Changed: Projects
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.obsidian/workspace.json
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@ -27,12 +27,26 @@
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@ -1180,7 +1180,7 @@
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"source": [
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"# To Do\n",
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"# Gruppenprojekt Medienwissenschaften - Analysing Facebook posts\n",
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"\n",
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"- More Explanation\n",
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"- Visulazation Excerxise\n",
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"<div style=\"display:flex;\">\n",
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" <div style=\"text-align: left\">\n",
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" Willkommen zum Gruppenprojekt Medienwissenschaften - Programmierübung Einführung in Python 3.\n",
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" </div>\n",
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" <img style=\"float: right; margin: 0px 15px 15px 0px\" src=\"https://www.python.org/static/img/python-logo-large.c36dccadd999.png?1576869008\" width=\"100\" />\n",
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"</div>\n",
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"\n",
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"Wenn Sie Fragen oder Verbesserungsvorschläge zum Inhalt oder Struktur der Notebooks haben, dann können sie eine E-Mail an Phil Keier ([p.keier@hbk-bs.de](mailto:p.keier@hbk-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) oder Martin Le ([martin.le@tu-bs.de](mailto:martin.le@tu-bs.de?subject=[SigSys]%20Feedback%20Programmierübung&)) schreiben.\n",
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"\n",
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"Link zu einem Python Spickzettel: [hier](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf)\n",
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"\n",
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"---"
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"source": [
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"# Analysing Facebook posts\n",
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"Social media plays an important role in people’s everyday life. The social media data has\n",
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"many uses, both in the business and social realm. Analysis of social media data would\n",
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"help us understand the crowd psychology and improve our business models.\n",
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"We are given a piece of data on Facebook’s popular posts. Please use Pandas to read the\n",
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"data set and perform the following analysis on the given data."
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"data set and perform the following analysis on the given data.\n",
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"\n",
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"Enclosed with this Notebook is the Dataset `facebook.csv`. Your task is to prove or disprove the following hypotheses.\n",
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"\n",
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"---"
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"id": "b3a7db87-762c-4c4e-9c6d-09dd896e8b4e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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"source": [
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"## Describe the Dataset\n",
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"\n",
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"Ask yourself the following questions:\n",
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"- What does the data tell us?\n",
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"- Which results can / cannot be drawn from the data?\n",
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"- Are the data normally distributed?"
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||||
" <td>Photo</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>8</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>3480</td>\n",
|
||||
" <td>6229</td>\n",
|
||||
" <td>537</td>\n",
|
||||
" <td>508</td>\n",
|
||||
" <td>687</td>\n",
|
||||
" <td>3961</td>\n",
|
||||
" <td>2104</td>\n",
|
||||
" <td>301</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>53.0</td>\n",
|
||||
" <td>22.0</td>\n",
|
||||
" <td>75</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>497</th>\n",
|
||||
" <td>81370</td>\n",
|
||||
" <td>Photo</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>3778</td>\n",
|
||||
" <td>7216</td>\n",
|
||||
" <td>625</td>\n",
|
||||
" <td>572</td>\n",
|
||||
" <td>795</td>\n",
|
||||
" <td>4742</td>\n",
|
||||
" <td>2388</td>\n",
|
||||
" <td>363</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>93.0</td>\n",
|
||||
" <td>18.0</td>\n",
|
||||
" <td>115</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>498</th>\n",
|
||||
" <td>81370</td>\n",
|
||||
" <td>Photo</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>11</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>4156</td>\n",
|
||||
" <td>7564</td>\n",
|
||||
" <td>626</td>\n",
|
||||
" <td>574</td>\n",
|
||||
" <td>832</td>\n",
|
||||
" <td>4534</td>\n",
|
||||
" <td>2452</td>\n",
|
||||
" <td>370</td>\n",
|
||||
" <td>7</td>\n",
|
||||
" <td>91.0</td>\n",
|
||||
" <td>38.0</td>\n",
|
||||
" <td>136</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>499</th>\n",
|
||||
" <td>81370</td>\n",
|
||||
" <td>Photo</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>4188</td>\n",
|
||||
" <td>7292</td>\n",
|
||||
" <td>564</td>\n",
|
||||
" <td>524</td>\n",
|
||||
" <td>743</td>\n",
|
||||
" <td>3861</td>\n",
|
||||
" <td>2200</td>\n",
|
||||
" <td>316</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>91.0</td>\n",
|
||||
" <td>28.0</td>\n",
|
||||
" <td>119</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>500 rows × 19 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Page total likes Type Category Post Month Post Weekday Post Hour \\\n",
|
||||
"0 139441 Photo 2 12 4 3 \n",
|
||||
"1 139441 Status 2 12 3 10 \n",
|
||||
"2 139441 Photo 3 12 3 3 \n",
|
||||
"3 139441 Photo 2 12 2 10 \n",
|
||||
"4 139441 Photo 2 12 2 3 \n",
|
||||
".. ... ... ... ... ... ... \n",
|
||||
"495 85093 Photo 3 1 7 2 \n",
|
||||
"496 81370 Photo 2 1 5 8 \n",
|
||||
"497 81370 Photo 1 1 5 2 \n",
|
||||
"498 81370 Photo 3 1 4 11 \n",
|
||||
"499 81370 Photo 2 1 4 4 \n",
|
||||
"\n",
|
||||
" Paid Lifetime Post Total Reach Lifetime Post Total Impressions \\\n",
|
||||
"0 0.0 2752 5091 \n",
|
||||
"1 0.0 10460 19057 \n",
|
||||
"2 0.0 2413 4373 \n",
|
||||
"3 1.0 50128 87991 \n",
|
||||
"4 0.0 7244 13594 \n",
|
||||
".. ... ... ... \n",
|
||||
"495 0.0 4684 7536 \n",
|
||||
"496 0.0 3480 6229 \n",
|
||||
"497 0.0 3778 7216 \n",
|
||||
"498 0.0 4156 7564 \n",
|
||||
"499 NaN 4188 7292 \n",
|
||||
"\n",
|
||||
" Lifetime Engaged Users Lifetime Post Consumers \\\n",
|
||||
"0 178 109 \n",
|
||||
"1 1457 1361 \n",
|
||||
"2 177 113 \n",
|
||||
"3 2211 790 \n",
|
||||
"4 671 410 \n",
|
||||
".. ... ... \n",
|
||||
"495 733 708 \n",
|
||||
"496 537 508 \n",
|
||||
"497 625 572 \n",
|
||||
"498 626 574 \n",
|
||||
"499 564 524 \n",
|
||||
"\n",
|
||||
" Lifetime Post Consumptions \\\n",
|
||||
"0 159 \n",
|
||||
"1 1674 \n",
|
||||
"2 154 \n",
|
||||
"3 1119 \n",
|
||||
"4 580 \n",
|
||||
".. ... \n",
|
||||
"495 985 \n",
|
||||
"496 687 \n",
|
||||
"497 795 \n",
|
||||
"498 832 \n",
|
||||
"499 743 \n",
|
||||
"\n",
|
||||
" Lifetime Post Impressions by people who have liked your Page \\\n",
|
||||
"0 3078 \n",
|
||||
"1 11710 \n",
|
||||
"2 2812 \n",
|
||||
"3 61027 \n",
|
||||
"4 6228 \n",
|
||||
".. ... \n",
|
||||
"495 4750 \n",
|
||||
"496 3961 \n",
|
||||
"497 4742 \n",
|
||||
"498 4534 \n",
|
||||
"499 3861 \n",
|
||||
"\n",
|
||||
" Lifetime Post reach by people who like your Page \\\n",
|
||||
"0 1640 \n",
|
||||
"1 6112 \n",
|
||||
"2 1503 \n",
|
||||
"3 32048 \n",
|
||||
"4 3200 \n",
|
||||
".. ... \n",
|
||||
"495 2876 \n",
|
||||
"496 2104 \n",
|
||||
"497 2388 \n",
|
||||
"498 2452 \n",
|
||||
"499 2200 \n",
|
||||
"\n",
|
||||
" Lifetime People who have liked your Page and engaged with your post \\\n",
|
||||
"0 119 \n",
|
||||
"1 1108 \n",
|
||||
"2 132 \n",
|
||||
"3 1386 \n",
|
||||
"4 396 \n",
|
||||
".. ... \n",
|
||||
"495 392 \n",
|
||||
"496 301 \n",
|
||||
"497 363 \n",
|
||||
"498 370 \n",
|
||||
"499 316 \n",
|
||||
"\n",
|
||||
" comment like share Total Interactions \n",
|
||||
"0 4 79.0 17.0 100 \n",
|
||||
"1 5 130.0 29.0 164 \n",
|
||||
"2 0 66.0 14.0 80 \n",
|
||||
"3 58 1572.0 147.0 1777 \n",
|
||||
"4 19 325.0 49.0 393 \n",
|
||||
".. ... ... ... ... \n",
|
||||
"495 5 53.0 26.0 84 \n",
|
||||
"496 0 53.0 22.0 75 \n",
|
||||
"497 4 93.0 18.0 115 \n",
|
||||
"498 7 91.0 38.0 136 \n",
|
||||
"499 0 91.0 28.0 119 \n",
|
||||
"\n",
|
||||
"[500 rows x 19 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 65,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# BEGIN SOLUTION\n",
|
||||
"data = pd.read_csv(\"dataset_Facebook.csv\", sep=\";\")\n",
|
||||
"data\n",
|
||||
"### BEGIN SOLUTION\n",
|
||||
"### END SOLUTION"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b5f2b0ff-e341-49d6-9928-d9448648e681",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade_id": "cell-1517dd4c342678e7",
|
||||
"locked": true,
|
||||
"schema_version": 3,
|
||||
"solution": false,
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Exercise 1\n",
|
||||
"Compute the mean and standard deviation of the number of likes for each type of post."
|
||||
"## H1: Paid posts = more interaction\n",
|
||||
"\n",
|
||||
"Paid contributions are more likely to be seen by many people. Among other things, more users interact with these posts. "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 63,
|
||||
"execution_count": 1,
|
||||
"id": "4a697468-fab6-499a-98a2-68dc5af7e516",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade": true,
|
||||
"grade_id": "cell-012b424d9de10c12",
|
||||
"locked": false,
|
||||
"points": 0,
|
||||
"schema_version": 3,
|
||||
"solution": true,
|
||||
"task": false
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"mean: \n",
|
||||
" {'Photo': like 182.611765\n",
|
||||
"dtype: float64, 'Status': like 176.711111\n",
|
||||
"dtype: float64, 'Link': like 73.318182\n",
|
||||
"dtype: float64, 'Video': like 231.428571\n",
|
||||
"dtype: float64} \n",
|
||||
" std: \n",
|
||||
" {'Photo': like 345.245233\n",
|
||||
"dtype: float64, 'Status': like 150.772499\n",
|
||||
"dtype: float64, 'Link': like 85.74624\n",
|
||||
"dtype: float64, 'Video': like 142.025652\n",
|
||||
"dtype: float64}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"### BEGIN SOLUTION\n",
|
||||
"type_of_posts = data[\"Type\"].unique()\n",
|
||||
"mean_likes = {}\n",
|
||||
"std_likes = {}\n",
|
||||
"for posts in type_of_posts:\n",
|
||||
" likes = data.loc[data[\"Type\"]==posts,[\"like\"]]\n",
|
||||
" mean_likes[posts] = likes.mean()\n",
|
||||
" std_likes[posts] = likes.std()\n",
|
||||
" # print(f\"The mean likes of type {posts} is {mean_likes} and standard deviation is {std_likes}\") \n",
|
||||
" \n",
|
||||
"print('mean: \\n', mean_likes, '\\n std: \\n', std_likes)\n",
|
||||
"### END SOLUTION"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b1b58071-43bd-42f0-9277-02de66cc5578",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade_id": "cell-9435c91c1af32ca3",
|
||||
"locked": true,
|
||||
"schema_version": 3,
|
||||
"solution": false,
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Exercise 2\n",
|
||||
"## H2: Paid Videos\n",
|
||||
"\n",
|
||||
"Find which time of day is most popular for posting based on the current data-set."
|
||||
"Videos are paid for more often and are shared more often. So it shows that advertising pays off. "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 78,
|
||||
"execution_count": 3,
|
||||
"id": "07d46bf8-5c69-40c9-8ea7-edbfe514f190",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade": true,
|
||||
"grade_id": "cell-3773d1ccd92283e4",
|
||||
"locked": false,
|
||||
"points": 0,
|
||||
"schema_version": 3,
|
||||
"solution": true,
|
||||
"task": false
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Post Month</th>\n",
|
||||
" <th>Post Weekday</th>\n",
|
||||
" <th>Post Hour</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>10</td>\n",
|
||||
" <td>7</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Post Month Post Weekday Post Hour\n",
|
||||
"0 10 7 3"
|
||||
]
|
||||
},
|
||||
"execution_count": 78,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"### BEGIN SOLUTION\n",
|
||||
"data[[\"Post Month\", \"Post Weekday\", \"Post Hour\"]].apply(lambda x: x.mode())\n",
|
||||
"### END SOLUTION"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a75a232c-ae0b-4d26-af16-ffcd06bbe40f",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade_id": "cell-5a54cabd55a2dfa0",
|
||||
"locked": true,
|
||||
"schema_version": 3,
|
||||
"solution": false,
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Exercise 3\n",
|
||||
"## H3: Top 2%\n",
|
||||
"\n",
|
||||
"Compute the difference of likes between paid and unpaid posts."
|
||||
"The top 2% of all posts were published in the afternoon on a Thursday. However, users interact with posts most frequently in the evening."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 101,
|
||||
"execution_count": 4,
|
||||
"id": "65311930-e7f5-4b9f-b30a-cd1769721b70",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade": true,
|
||||
"grade_id": "cell-23e55e763d064166",
|
||||
"locked": false,
|
||||
"points": 0,
|
||||
"schema_version": 3,
|
||||
"solution": true,
|
||||
"task": false
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Total likes on paid posts are like 32755.0\n",
|
||||
"dtype: float64 and the total likes on unpaid posts are like 56040.0\n",
|
||||
"dtype: float64 and the difference between likes is like 23285.0\n",
|
||||
"dtype: float64.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"### BEGIN SOLUTION\n",
|
||||
"likes_paid = data.loc[data[\"Paid\"]==1.0, [\"like\"]].sum()\n",
|
||||
"total_likes = data[\"like\"].sum()\n",
|
||||
"likes_unpaid = total_likes - likes_paid\n",
|
||||
"print(f\"Total likes on paid posts are {likes_paid} and the total likes on unpaid posts are {likes_unpaid} and the difference between likes is {abs(likes_paid-likes_unpaid)}.\")\n",
|
||||
"### END SOLUTION"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c480d5b4-8dcc-46ed-9318-6b479ee7d4f5",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
"grade": false,
|
||||
"grade_id": "cell-08fb67d9e3a7d1d4",
|
||||
"locked": true,
|
||||
"schema_version": 3,
|
||||
"solution": false,
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"## Exercise 4\n",
|
||||
"Compute the correlation between ”Lifetime Post Total Reach” and ”Lifetime Post\n",
|
||||
"Total Impression”."
|
||||
"## Simulate Posts\n",
|
||||
"\n",
|
||||
"Use the available data to apply an accurate simulation. Describe which properties a post must have in order to maximize its likes."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 104,
|
||||
"execution_count": 5,
|
||||
"id": "cb9eee29-943d-40fa-9551-d8749a906509",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
@ -670,19 +255,9 @@
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"correlation between the 2 columns is 0.6949263153309504\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"### BEGIN SOLUTION\n",
|
||||
"corr = data[\"Lifetime Post Total Reach\"].corr(data[\"Lifetime Post Total Impressions\"])\n",
|
||||
"print(f\"correlation between the 2 columns is {corr}\")\n",
|
||||
"### END SOLUTION"
|
||||
]
|
||||
}
|
||||
@ -703,7 +278,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.16"
|
||||
"version": "3.12.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -29,63 +29,6 @@
|
||||
"* Draw insights by visualizing these relationships"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7122680a-8b1d-482a-9080-8276bf0a3d12",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"\n",
|
||||
"- [ ] Erhöhung der Dichte der Fahrten\n",
|
||||
"- [ ] Zuordnung Tag, Zeit und Zeitzone klären\n",
|
||||
"- [ ] Dichte der Fahrten - länge und Anzahl deutlicher herausarbeiten\n",
|
||||
"- [ ] Dichte nach Ort (x,y) auf Maps? - Folium einbinden \n",
|
||||
"\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "8b342eb8-81eb-4363-a333-5af25a442337",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Import Libraries"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "15a54b8d-5fa0-4541-bfaf-d543a757444d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Reading Datasets"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "5ecdaa56-f420-4cbb-98c9-3b4a34504dff",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Transform Datasets"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ab423532-e03e-4388-8cd7-5b6b2110f4f5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Plotting\n",
|
||||
"\n",
|
||||
"### Bar Plots\n",
|
||||
"\n",
|
||||
"### Folium"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2c0c850b-8da6-4b31-b56d-aed5bd689a97",
|
||||
"metadata": {},
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1b38edc7",
|
||||
@ -114,7 +57,8 @@
|
||||
" * Identify the most and least busy day of the week\n",
|
||||
"* Plot (bar plot) density of rides per hour\n",
|
||||
" * Idensity the hours with the highest and least number of rides\n",
|
||||
"* Plot (scatter plot) density of rides per location"
|
||||
"* Plot (scatter plot) density of rides per location\n",
|
||||
"* Use Foliums Polyline Feature to Map out the Trips"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -551,7 +495,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.16"
|
||||
"version": "3.12.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -858,7 +858,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.12.7"
|
||||
"version": "3.12.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
66
Material/wise_24_25/Shuffle Groups.ipynb
Normal file
66
Material/wise_24_25/Shuffle Groups.ipynb
Normal file
@ -0,0 +1,66 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"id": "dd4643e9-5b2f-4227-8f2c-de0c397750c2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'1. MeWi 1': 'Facebook Data',\n",
|
||||
" '2. MeWi 2': 'Uber Trips',\n",
|
||||
" '3. MeWi 3': 'Discovery of Handwashing',\n",
|
||||
" '4. MeWi 4': 'Uber Trips',\n",
|
||||
" '5. MeWi 5': 'Covid-19',\n",
|
||||
" '6. MeWi 6': 'Extramarital Affairs',\n",
|
||||
" '7. DiKum': 'Hochschulstatistik'}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"from pprint import pprint\n",
|
||||
"\n",
|
||||
"# Setup\n",
|
||||
"rng = np.random.default_rng()\n",
|
||||
"projects = [\"Discovery of Handwashing\", \"Facebook Data\", \"Covid-19\", \"Hochschulstatistik\", \"Uber Trips\", \"Extramarital Affairs\"]\n",
|
||||
"groups = [f\"{n}. MeWi {n}\" for n in range(1,7)]\n",
|
||||
"groups.append(\"7. DiKum\")\n",
|
||||
"\n",
|
||||
"# Shuffle\n",
|
||||
"rng_index = np.random.randint(len(projects))\n",
|
||||
"projects.append(projects[rng_index])\n",
|
||||
"rng.shuffle(projects)\n",
|
||||
"rng.shuffle(groups)\n",
|
||||
"\n",
|
||||
"# Pretty Print\n",
|
||||
"data = {group: project for group, project in zip(groups, projects)}\n",
|
||||
"pprint(data)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.12.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@ -82,7 +82,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"execution_count": 2,
|
||||
"id": "8e24289e-a738-4ae4-a6d4-a936263120fc",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
@ -95,7 +95,861 @@
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Zeitstempel</th>\n",
|
||||
" <th>Wie Alt bist du?</th>\n",
|
||||
" <th>Bewerte deine bisherige Erfahrung mit Gruppenarbeiten an der Universität</th>\n",
|
||||
" <th>Welches Geschlecht hast du?</th>\n",
|
||||
" <th>Was studieren du?</th>\n",
|
||||
" <th>Auf einer Skala von 1-5 (1 - absolut unzufrieden, 5 - absolut zufrieden), wie beurteilst du deinen Studiengang?</th>\n",
|
||||
" <th>Nutzt du ein Smartphone?</th>\n",
|
||||
" <th>Wenn Ja, von welcher Marke ist ihr Smartphone?</th>\n",
|
||||
" <th>Bewerte die allgemeine Politische Situation in Deutschland.</th>\n",
|
||||
" <th>Auf einer Skala von 1-5 (1 - Sehr gut, 5 - Garnicht), wie gut schätzen du dich selbst ein die Programmiersprache Python zu beherrschen ?</th>\n",
|
||||
" <th>Besitzen du einen Heimrechner (Laptop, Standrechner, etc.; Kein Smartphone!)</th>\n",
|
||||
" <th>Wenn Ja, welches Betriebsystem verwendst du?</th>\n",
|
||||
" <th>Ich habe mich (in meinem bisherigen leben) mindestens einmal strukturell benachteiligt gefühlt.</th>\n",
|
||||
" <th>Auf einer Skala von 1-5 (5 Sehr gut, 1 Garnicht), wie gut schätz du dich selbst ein Programmieren zu können?</th>\n",
|
||||
" <th>Ich komme aus...</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2025/01/17 3:01:58 PM MEZ</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2025/01/17 3:02:20 PM MEZ</td>\n",
|
||||
" <td>23</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Einem sehr gut situierten Haushalt</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2025/01/17 3:02:20 PM MEZ</td>\n",
|
||||
" <td>30</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Männlich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2025/01/17 3:02:24 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2025/01/17 3:02:26 PM MEZ</td>\n",
|
||||
" <td>27</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Samsung</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>ärmlichen Verhältnissen</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5</th>\n",
|
||||
" <td>2025/01/17 3:02:31 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>2025/01/17 3:02:43 PM MEZ</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7</th>\n",
|
||||
" <td>2025/01/17 3:02:44 PM MEZ</td>\n",
|
||||
" <td>23</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>8</th>\n",
|
||||
" <td>2025/01/17 3:02:46 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>9</th>\n",
|
||||
" <td>2025/01/17 3:02:58 PM MEZ</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>ärmlichen Verhältnissen</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10</th>\n",
|
||||
" <td>2025/01/17 3:02:59 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>11</th>\n",
|
||||
" <td>2025/01/17 3:03:00 PM MEZ</td>\n",
|
||||
" <td>24</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>12</th>\n",
|
||||
" <td>2025/01/17 3:03:07 PM MEZ</td>\n",
|
||||
" <td>25</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>13</th>\n",
|
||||
" <td>2025/01/17 3:03:14 PM MEZ</td>\n",
|
||||
" <td>24</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>14</th>\n",
|
||||
" <td>2025/01/17 3:03:18 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>15</th>\n",
|
||||
" <td>2025/01/17 3:03:26 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>16</th>\n",
|
||||
" <td>2025/01/17 3:03:28 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Einem sehr gut situierten Haushalt</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17</th>\n",
|
||||
" <td>2025/01/17 3:03:31 PM MEZ</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>18</th>\n",
|
||||
" <td>2025/01/17 3:03:31 PM MEZ</td>\n",
|
||||
" <td>20</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>19</th>\n",
|
||||
" <td>2025/01/17 3:04:07 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>20</th>\n",
|
||||
" <td>2025/01/17 3:04:11 PM MEZ</td>\n",
|
||||
" <td>23</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>21</th>\n",
|
||||
" <td>2025/01/17 3:04:13 PM MEZ</td>\n",
|
||||
" <td>26</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Männlich</td>\n",
|
||||
" <td>Sonstige</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 10</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>22</th>\n",
|
||||
" <td>2025/01/17 3:07:39 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>23</th>\n",
|
||||
" <td>2025/01/17 3:11:27 PM MEZ</td>\n",
|
||||
" <td>204</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Apple</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Mac OS</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>ärmlichen Verhältnissen</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>24</th>\n",
|
||||
" <td>2025/01/17 3:11:54 PM MEZ</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Xiaomi</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>25</th>\n",
|
||||
" <td>2025/01/17 3:49:36 PM MEZ</td>\n",
|
||||
" <td>19</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Weiblich</td>\n",
|
||||
" <td>Medienwissenschaften</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Samsung</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Ja</td>\n",
|
||||
" <td>Windows 11</td>\n",
|
||||
" <td>Nein</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>dem normalem Mittelstand</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Zeitstempel Wie Alt bist du? \\\n",
|
||||
"0 2025/01/17 3:01:58 PM MEZ 22 \n",
|
||||
"1 2025/01/17 3:02:20 PM MEZ 23 \n",
|
||||
"2 2025/01/17 3:02:20 PM MEZ 30 \n",
|
||||
"3 2025/01/17 3:02:24 PM MEZ 21 \n",
|
||||
"4 2025/01/17 3:02:26 PM MEZ 27 \n",
|
||||
"5 2025/01/17 3:02:31 PM MEZ 21 \n",
|
||||
"6 2025/01/17 3:02:43 PM MEZ 22 \n",
|
||||
"7 2025/01/17 3:02:44 PM MEZ 23 \n",
|
||||
"8 2025/01/17 3:02:46 PM MEZ 21 \n",
|
||||
"9 2025/01/17 3:02:58 PM MEZ 22 \n",
|
||||
"10 2025/01/17 3:02:59 PM MEZ 21 \n",
|
||||
"11 2025/01/17 3:03:00 PM MEZ 24 \n",
|
||||
"12 2025/01/17 3:03:07 PM MEZ 25 \n",
|
||||
"13 2025/01/17 3:03:14 PM MEZ 24 \n",
|
||||
"14 2025/01/17 3:03:18 PM MEZ 21 \n",
|
||||
"15 2025/01/17 3:03:26 PM MEZ 21 \n",
|
||||
"16 2025/01/17 3:03:28 PM MEZ 21 \n",
|
||||
"17 2025/01/17 3:03:31 PM MEZ 22 \n",
|
||||
"18 2025/01/17 3:03:31 PM MEZ 20 \n",
|
||||
"19 2025/01/17 3:04:07 PM MEZ 21 \n",
|
||||
"20 2025/01/17 3:04:11 PM MEZ 23 \n",
|
||||
"21 2025/01/17 3:04:13 PM MEZ 26 \n",
|
||||
"22 2025/01/17 3:07:39 PM MEZ 21 \n",
|
||||
"23 2025/01/17 3:11:27 PM MEZ 204 \n",
|
||||
"24 2025/01/17 3:11:54 PM MEZ 21 \n",
|
||||
"25 2025/01/17 3:49:36 PM MEZ 19 \n",
|
||||
"\n",
|
||||
" Bewerte deine bisherige Erfahrung mit Gruppenarbeiten an der Universität \\\n",
|
||||
"0 3 \n",
|
||||
"1 3 \n",
|
||||
"2 3 \n",
|
||||
"3 4 \n",
|
||||
"4 4 \n",
|
||||
"5 2 \n",
|
||||
"6 2 \n",
|
||||
"7 3 \n",
|
||||
"8 3 \n",
|
||||
"9 2 \n",
|
||||
"10 4 \n",
|
||||
"11 3 \n",
|
||||
"12 4 \n",
|
||||
"13 3 \n",
|
||||
"14 3 \n",
|
||||
"15 3 \n",
|
||||
"16 2 \n",
|
||||
"17 4 \n",
|
||||
"18 3 \n",
|
||||
"19 3 \n",
|
||||
"20 3 \n",
|
||||
"21 3 \n",
|
||||
"22 4 \n",
|
||||
"23 3 \n",
|
||||
"24 3 \n",
|
||||
"25 3 \n",
|
||||
"\n",
|
||||
" Welches Geschlecht hast du? Was studieren du? \\\n",
|
||||
"0 Weiblich Medienwissenschaften \n",
|
||||
"1 Weiblich Medienwissenschaften \n",
|
||||
"2 Männlich Medienwissenschaften \n",
|
||||
"3 Weiblich Medienwissenschaften \n",
|
||||
"4 Weiblich Medienwissenschaften \n",
|
||||
"5 Weiblich Sonstige \n",
|
||||
"6 Weiblich Medienwissenschaften \n",
|
||||
"7 Weiblich Sonstige \n",
|
||||
"8 Weiblich Medienwissenschaften \n",
|
||||
"9 Weiblich Medienwissenschaften \n",
|
||||
"10 Weiblich Medienwissenschaften \n",
|
||||
"11 Weiblich Medienwissenschaften \n",
|
||||
"12 Weiblich Medienwissenschaften \n",
|
||||
"13 Weiblich Medienwissenschaften \n",
|
||||
"14 Weiblich Medienwissenschaften \n",
|
||||
"15 Weiblich Medienwissenschaften \n",
|
||||
"16 Weiblich Medienwissenschaften \n",
|
||||
"17 Weiblich Medienwissenschaften \n",
|
||||
"18 Weiblich Medienwissenschaften \n",
|
||||
"19 Weiblich Sonstige \n",
|
||||
"20 Weiblich Sonstige \n",
|
||||
"21 Männlich Sonstige \n",
|
||||
"22 Weiblich Medienwissenschaften \n",
|
||||
"23 Weiblich Medienwissenschaften \n",
|
||||
"24 Weiblich Medienwissenschaften \n",
|
||||
"25 Weiblich Medienwissenschaften \n",
|
||||
"\n",
|
||||
" Auf einer Skala von 1-5 (1 - absolut unzufrieden, 5 - absolut zufrieden), wie beurteilst du deinen Studiengang? \\\n",
|
||||
"0 2 \n",
|
||||
"1 4 \n",
|
||||
"2 3 \n",
|
||||
"3 3 \n",
|
||||
"4 2 \n",
|
||||
"5 4 \n",
|
||||
"6 3 \n",
|
||||
"7 3 \n",
|
||||
"8 3 \n",
|
||||
"9 3 \n",
|
||||
"10 3 \n",
|
||||
"11 3 \n",
|
||||
"12 3 \n",
|
||||
"13 3 \n",
|
||||
"14 3 \n",
|
||||
"15 3 \n",
|
||||
"16 2 \n",
|
||||
"17 5 \n",
|
||||
"18 3 \n",
|
||||
"19 4 \n",
|
||||
"20 4 \n",
|
||||
"21 4 \n",
|
||||
"22 4 \n",
|
||||
"23 3 \n",
|
||||
"24 4 \n",
|
||||
"25 3 \n",
|
||||
"\n",
|
||||
" Nutzt du ein Smartphone? Wenn Ja, von welcher Marke ist ihr Smartphone? \\\n",
|
||||
"0 Ja Apple \n",
|
||||
"1 Ja Apple \n",
|
||||
"2 Ja Sonstige \n",
|
||||
"3 Ja Apple \n",
|
||||
"4 Ja Samsung \n",
|
||||
"5 Ja Apple \n",
|
||||
"6 Ja Apple \n",
|
||||
"7 Ja Sonstige \n",
|
||||
"8 Ja Apple \n",
|
||||
"9 Ja Apple \n",
|
||||
"10 Ja Apple \n",
|
||||
"11 Ja Apple \n",
|
||||
"12 Ja Apple \n",
|
||||
"13 Ja Apple \n",
|
||||
"14 Ja Apple \n",
|
||||
"15 Ja Apple \n",
|
||||
"16 Ja Apple \n",
|
||||
"17 Ja Apple \n",
|
||||
"18 Ja Apple \n",
|
||||
"19 Ja Apple \n",
|
||||
"20 Ja Apple \n",
|
||||
"21 Ja Apple \n",
|
||||
"22 Ja Apple \n",
|
||||
"23 Ja Apple \n",
|
||||
"24 Ja Xiaomi \n",
|
||||
"25 Ja Samsung \n",
|
||||
"\n",
|
||||
" Bewerte die allgemeine Politische Situation in Deutschland. \\\n",
|
||||
"0 1 \n",
|
||||
"1 2 \n",
|
||||
"2 3 \n",
|
||||
"3 2 \n",
|
||||
"4 2 \n",
|
||||
"5 3 \n",
|
||||
"6 2 \n",
|
||||
"7 2 \n",
|
||||
"8 2 \n",
|
||||
"9 2 \n",
|
||||
"10 2 \n",
|
||||
"11 1 \n",
|
||||
"12 2 \n",
|
||||
"13 1 \n",
|
||||
"14 3 \n",
|
||||
"15 2 \n",
|
||||
"16 3 \n",
|
||||
"17 3 \n",
|
||||
"18 2 \n",
|
||||
"19 2 \n",
|
||||
"20 1 \n",
|
||||
"21 2 \n",
|
||||
"22 2 \n",
|
||||
"23 2 \n",
|
||||
"24 3 \n",
|
||||
"25 3 \n",
|
||||
"\n",
|
||||
" Auf einer Skala von 1-5 (1 - Sehr gut, 5 - Garnicht), wie gut schätzen du dich selbst ein die Programmiersprache Python zu beherrschen ? \\\n",
|
||||
"0 3 \n",
|
||||
"1 4 \n",
|
||||
"2 3 \n",
|
||||
"3 4 \n",
|
||||
"4 4 \n",
|
||||
"5 4 \n",
|
||||
"6 5 \n",
|
||||
"7 3 \n",
|
||||
"8 4 \n",
|
||||
"9 4 \n",
|
||||
"10 4 \n",
|
||||
"11 3 \n",
|
||||
"12 3 \n",
|
||||
"13 3 \n",
|
||||
"14 4 \n",
|
||||
"15 4 \n",
|
||||
"16 2 \n",
|
||||
"17 4 \n",
|
||||
"18 4 \n",
|
||||
"19 3 \n",
|
||||
"20 3 \n",
|
||||
"21 3 \n",
|
||||
"22 3 \n",
|
||||
"23 4 \n",
|
||||
"24 3 \n",
|
||||
"25 4 \n",
|
||||
"\n",
|
||||
" Besitzen du einen Heimrechner (Laptop, Standrechner, etc.; Kein Smartphone!) \\\n",
|
||||
"0 Ja \n",
|
||||
"1 Ja \n",
|
||||
"2 Ja \n",
|
||||
"3 Ja \n",
|
||||
"4 Ja \n",
|
||||
"5 Ja \n",
|
||||
"6 Ja \n",
|
||||
"7 Ja \n",
|
||||
"8 Ja \n",
|
||||
"9 Ja \n",
|
||||
"10 Ja \n",
|
||||
"11 Ja \n",
|
||||
"12 Ja \n",
|
||||
"13 Ja \n",
|
||||
"14 Ja \n",
|
||||
"15 Ja \n",
|
||||
"16 Ja \n",
|
||||
"17 Ja \n",
|
||||
"18 Ja \n",
|
||||
"19 Ja \n",
|
||||
"20 Ja \n",
|
||||
"21 Ja \n",
|
||||
"22 Ja \n",
|
||||
"23 Ja \n",
|
||||
"24 Ja \n",
|
||||
"25 Ja \n",
|
||||
"\n",
|
||||
" Wenn Ja, welches Betriebsystem verwendst du? \\\n",
|
||||
"0 Windows 11 \n",
|
||||
"1 Mac OS \n",
|
||||
"2 Windows 11 \n",
|
||||
"3 Mac OS \n",
|
||||
"4 Mac OS \n",
|
||||
"5 Mac OS \n",
|
||||
"6 Mac OS \n",
|
||||
"7 Mac OS \n",
|
||||
"8 Windows 11 \n",
|
||||
"9 Windows 11 \n",
|
||||
"10 Windows 11 \n",
|
||||
"11 Windows 10 \n",
|
||||
"12 Windows 10 \n",
|
||||
"13 Mac OS \n",
|
||||
"14 Mac OS \n",
|
||||
"15 Windows 10 \n",
|
||||
"16 Mac OS \n",
|
||||
"17 Windows 10 \n",
|
||||
"18 Windows 10 \n",
|
||||
"19 Windows 11 \n",
|
||||
"20 Mac OS \n",
|
||||
"21 Windows 10 \n",
|
||||
"22 Mac OS \n",
|
||||
"23 Mac OS \n",
|
||||
"24 Windows 11 \n",
|
||||
"25 Windows 11 \n",
|
||||
"\n",
|
||||
" Ich habe mich (in meinem bisherigen leben) mindestens einmal strukturell benachteiligt gefühlt. \\\n",
|
||||
"0 Ja \n",
|
||||
"1 Ja \n",
|
||||
"2 Nein \n",
|
||||
"3 Ja \n",
|
||||
"4 Ja \n",
|
||||
"5 Nein \n",
|
||||
"6 Ja \n",
|
||||
"7 Ja \n",
|
||||
"8 Ja \n",
|
||||
"9 Ja \n",
|
||||
"10 Ja \n",
|
||||
"11 Nein \n",
|
||||
"12 Ja \n",
|
||||
"13 Ja \n",
|
||||
"14 Ja \n",
|
||||
"15 Nein \n",
|
||||
"16 Nein \n",
|
||||
"17 Ja \n",
|
||||
"18 Nein \n",
|
||||
"19 Ja \n",
|
||||
"20 Ja \n",
|
||||
"21 Ja \n",
|
||||
"22 Ja \n",
|
||||
"23 Ja \n",
|
||||
"24 Nein \n",
|
||||
"25 Nein \n",
|
||||
"\n",
|
||||
" Auf einer Skala von 1-5 (5 Sehr gut, 1 Garnicht), wie gut schätz du dich selbst ein Programmieren zu können? \\\n",
|
||||
"0 2 \n",
|
||||
"1 2 \n",
|
||||
"2 3 \n",
|
||||
"3 4 \n",
|
||||
"4 3 \n",
|
||||
"5 4 \n",
|
||||
"6 1 \n",
|
||||
"7 3 \n",
|
||||
"8 2 \n",
|
||||
"9 2 \n",
|
||||
"10 2 \n",
|
||||
"11 1 \n",
|
||||
"12 3 \n",
|
||||
"13 3 \n",
|
||||
"14 2 \n",
|
||||
"15 2 \n",
|
||||
"16 3 \n",
|
||||
"17 2 \n",
|
||||
"18 2 \n",
|
||||
"19 2 \n",
|
||||
"20 3 \n",
|
||||
"21 3 \n",
|
||||
"22 2 \n",
|
||||
"23 1 \n",
|
||||
"24 2 \n",
|
||||
"25 3 \n",
|
||||
"\n",
|
||||
" Ich komme aus... \n",
|
||||
"0 dem normalem Mittelstand \n",
|
||||
"1 Einem sehr gut situierten Haushalt \n",
|
||||
"2 dem normalem Mittelstand \n",
|
||||
"3 dem normalem Mittelstand \n",
|
||||
"4 ärmlichen Verhältnissen \n",
|
||||
"5 dem normalem Mittelstand \n",
|
||||
"6 dem normalem Mittelstand \n",
|
||||
"7 dem normalem Mittelstand \n",
|
||||
"8 dem normalem Mittelstand \n",
|
||||
"9 ärmlichen Verhältnissen \n",
|
||||
"10 dem normalem Mittelstand \n",
|
||||
"11 dem normalem Mittelstand \n",
|
||||
"12 dem normalem Mittelstand \n",
|
||||
"13 dem normalem Mittelstand \n",
|
||||
"14 dem normalem Mittelstand \n",
|
||||
"15 dem normalem Mittelstand \n",
|
||||
"16 Einem sehr gut situierten Haushalt \n",
|
||||
"17 dem normalem Mittelstand \n",
|
||||
"18 dem normalem Mittelstand \n",
|
||||
"19 dem normalem Mittelstand \n",
|
||||
"20 dem normalem Mittelstand \n",
|
||||
"21 dem normalem Mittelstand \n",
|
||||
"22 dem normalem Mittelstand \n",
|
||||
"23 ärmlichen Verhältnissen \n",
|
||||
"24 dem normalem Mittelstand \n",
|
||||
"25 dem normalem Mittelstand "
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"### BEGIN SOLUTION\n",
|
||||
"### END SOLUTION"
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Binary file not shown.
@ -1266,7 +1266,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 20,
|
||||
"execution_count": 2,
|
||||
"id": "8bc69bfc-96aa-4fdf-b540-a956ff4c1baf",
|
||||
"metadata": {
|
||||
"nbgrader": {
|
||||
@ -1279,10 +1279,157 @@
|
||||
"task": false
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Geschlecht</th>\n",
|
||||
" <th>Branche</th>\n",
|
||||
" <th>Verdienst</th>\n",
|
||||
" <th>Verdienstart</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>weiblich</td>\n",
|
||||
" <td>Metalloberflächenbehandlung</td>\n",
|
||||
" <td>16.19</td>\n",
|
||||
" <td>Mittlere Bruttostundenverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>weiblich</td>\n",
|
||||
" <td>Metalloberflächenbehandlung</td>\n",
|
||||
" <td>2810.00</td>\n",
|
||||
" <td>Durchschn. Bruttomonatsverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>weiblich</td>\n",
|
||||
" <td>Metalloberflächenbehandlung</td>\n",
|
||||
" <td>17.28</td>\n",
|
||||
" <td>Durchschn. Bruttostundenverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>weiblich</td>\n",
|
||||
" <td>Metalloberflächenbehandlung</td>\n",
|
||||
" <td>2705.00</td>\n",
|
||||
" <td>Mittlere Bruttomonatsverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>männlich</td>\n",
|
||||
" <td>Nicht ärztliche Therapie und Heilkunde</td>\n",
|
||||
" <td>18.99</td>\n",
|
||||
" <td>Mittlere Bruttostundenverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17767</th>\n",
|
||||
" <td>Insgesamt</td>\n",
|
||||
" <td>Rohstoffgewinn, Glas-, Keramikverarbeitung</td>\n",
|
||||
" <td>3181.00</td>\n",
|
||||
" <td>Mittlere Bruttomonatsverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17768</th>\n",
|
||||
" <td>Insgesamt</td>\n",
|
||||
" <td>Nichtmed. Gesundheit, Körperpfl., Medizintechnik</td>\n",
|
||||
" <td>19.63</td>\n",
|
||||
" <td>Mittlere Bruttostundenverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17769</th>\n",
|
||||
" <td>Insgesamt</td>\n",
|
||||
" <td>Nichtmed. Gesundheit, Körperpfl., Medizintechnik</td>\n",
|
||||
" <td>3373.00</td>\n",
|
||||
" <td>Durchschn. Bruttomonatsverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17770</th>\n",
|
||||
" <td>Insgesamt</td>\n",
|
||||
" <td>Nichtmed. Gesundheit, Körperpfl., Medizintechnik</td>\n",
|
||||
" <td>20.74</td>\n",
|
||||
" <td>Durchschn. Bruttostundenverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>17771</th>\n",
|
||||
" <td>Insgesamt</td>\n",
|
||||
" <td>Nichtmed. Gesundheit, Körperpfl., Medizintechnik</td>\n",
|
||||
" <td>3201.00</td>\n",
|
||||
" <td>Mittlere Bruttomonatsverdienste ohne Sonderz.</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>17772 rows × 4 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Geschlecht Branche Verdienst \\\n",
|
||||
"0 weiblich Metalloberflächenbehandlung 16.19 \n",
|
||||
"1 weiblich Metalloberflächenbehandlung 2810.00 \n",
|
||||
"2 weiblich Metalloberflächenbehandlung 17.28 \n",
|
||||
"3 weiblich Metalloberflächenbehandlung 2705.00 \n",
|
||||
"4 männlich Nicht ärztliche Therapie und Heilkunde 18.99 \n",
|
||||
"... ... ... ... \n",
|
||||
"17767 Insgesamt Rohstoffgewinn, Glas-, Keramikverarbeitung 3181.00 \n",
|
||||
"17768 Insgesamt Nichtmed. Gesundheit, Körperpfl., Medizintechnik 19.63 \n",
|
||||
"17769 Insgesamt Nichtmed. Gesundheit, Körperpfl., Medizintechnik 3373.00 \n",
|
||||
"17770 Insgesamt Nichtmed. Gesundheit, Körperpfl., Medizintechnik 20.74 \n",
|
||||
"17771 Insgesamt Nichtmed. Gesundheit, Körperpfl., Medizintechnik 3201.00 \n",
|
||||
"\n",
|
||||
" Verdienstart \n",
|
||||
"0 Mittlere Bruttostundenverdienste ohne Sonderz. \n",
|
||||
"1 Durchschn. Bruttomonatsverdienste ohne Sonderz. \n",
|
||||
"2 Durchschn. Bruttostundenverdienste ohne Sonderz. \n",
|
||||
"3 Mittlere Bruttomonatsverdienste ohne Sonderz. \n",
|
||||
"4 Mittlere Bruttostundenverdienste ohne Sonderz. \n",
|
||||
"... ... \n",
|
||||
"17767 Mittlere Bruttomonatsverdienste ohne Sonderz. \n",
|
||||
"17768 Mittlere Bruttostundenverdienste ohne Sonderz. \n",
|
||||
"17769 Durchschn. Bruttomonatsverdienste ohne Sonderz. \n",
|
||||
"17770 Durchschn. Bruttostundenverdienste ohne Sonderz. \n",
|
||||
"17771 Mittlere Bruttomonatsverdienste ohne Sonderz. \n",
|
||||
"\n",
|
||||
"[17772 rows x 4 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# BEGIN SOLUTION\n",
|
||||
"import pandas as pd\n",
|
||||
"dataset: pd.DataFrame = pd.read_csv('bruttoverdiensterhebung_deutschland_april_22-23_nach_geschlecht.csv')\n",
|
||||
"dataset\n",
|
||||
"# END SOLUTION"
|
||||
]
|
||||
},
|
||||
|
||||
27
Material/wise_24_25/lernmaterial/survey.csv
Normal file
27
Material/wise_24_25/lernmaterial/survey.csv
Normal file
@ -0,0 +1,27 @@
|
||||
"Zeitstempel","Wie Alt bist du?","Bewerte deine bisherige Erfahrung mit Gruppenarbeiten an der Universität","Welches Geschlecht hast du?","Was studieren du?","Auf einer Skala von 1-5 (1 - absolut unzufrieden, 5 - absolut zufrieden), wie beurteilst du deinen Studiengang?","Nutzt du ein Smartphone?","Wenn Ja, von welcher Marke ist ihr Smartphone?","Bewerte die allgemeine Politische Situation in Deutschland.","Auf einer Skala von 1-5 (1 - Sehr gut, 5 - Garnicht), wie gut schätzen du dich selbst ein die Programmiersprache Python zu beherrschen ?","Besitzen du einen Heimrechner (Laptop, Standrechner, etc.; Kein Smartphone!)","Wenn Ja, welches Betriebsystem verwendst du?","Ich habe mich (in meinem bisherigen leben) mindestens einmal strukturell benachteiligt gefühlt.","Auf einer Skala von 1-5 (5 Sehr gut, 1 Garnicht), wie gut schätz du dich selbst ein Programmieren zu können?","Ich komme aus..."
|
||||
"2025/01/17 3:01:58 PM MEZ","22","3","Weiblich","Medienwissenschaften","2","Ja","Apple","1","3","Ja","Windows 11","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:20 PM MEZ","23","3","Weiblich","Medienwissenschaften","4","Ja","Apple","2","4","Ja","Mac OS","Ja","2","Einem sehr gut situierten Haushalt"
|
||||
"2025/01/17 3:02:20 PM MEZ","30","3","Männlich","Medienwissenschaften","3","Ja","Sonstige","3","3","Ja","Windows 11","Nein","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:24 PM MEZ","21","4","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Mac OS","Ja","4","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:26 PM MEZ","27","4","Weiblich","Medienwissenschaften","2","Ja","Samsung","2","4","Ja","Mac OS","Ja","3","ärmlichen Verhältnissen"
|
||||
"2025/01/17 3:02:31 PM MEZ","21","2","Weiblich","Sonstige","4","Ja","Apple","3","4","Ja","Mac OS","Nein","4","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:43 PM MEZ","22","2","Weiblich","Medienwissenschaften","3","Ja","Apple","2","5","Ja","Mac OS","Ja","1","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:44 PM MEZ","23","3","Weiblich","Sonstige","3","Ja","Sonstige","2","3","Ja","Mac OS","Ja","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:46 PM MEZ","21","3","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Windows 11","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:02:58 PM MEZ","22","2","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Windows 11","Ja","2","ärmlichen Verhältnissen"
|
||||
"2025/01/17 3:02:59 PM MEZ","21","4","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Windows 11","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:00 PM MEZ","24","3","Weiblich","Medienwissenschaften","3","Ja","Apple","1","3","Ja","Windows 10","Nein","1","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:07 PM MEZ","25","4","Weiblich","Medienwissenschaften","3","Ja","Apple","2","3","Ja","Windows 10","Ja","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:14 PM MEZ","24","3","Weiblich","Medienwissenschaften","3","Ja","Apple","1","3","Ja","Mac OS","Ja","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:18 PM MEZ","21","3","Weiblich","Medienwissenschaften","3","Ja","Apple","3","4","Ja","Mac OS","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:26 PM MEZ","21","3","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Windows 10","Nein","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:28 PM MEZ","21","2","Weiblich","Medienwissenschaften","2","Ja","Apple","3","2","Ja","Mac OS","Nein","3","Einem sehr gut situierten Haushalt"
|
||||
"2025/01/17 3:03:31 PM MEZ","22","4","Weiblich","Medienwissenschaften","5","Ja","Apple","3","4","Ja","Windows 10","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:03:31 PM MEZ","20","3","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Windows 10","Nein","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:04:07 PM MEZ","21","3","Weiblich","Sonstige","4","Ja","Apple","2","3","Ja","Windows 11","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:04:11 PM MEZ","23","3","Weiblich","Sonstige","4","Ja","Apple","1","3","Ja","Mac OS","Ja","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:04:13 PM MEZ","26","3","Männlich","Sonstige","4","Ja","Apple","2","3","Ja","Windows 10","Ja","3","dem normalem Mittelstand"
|
||||
"2025/01/17 3:07:39 PM MEZ","21","4","Weiblich","Medienwissenschaften","4","Ja","Apple","2","3","Ja","Mac OS","Ja","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:11:27 PM MEZ","204","3","Weiblich","Medienwissenschaften","3","Ja","Apple","2","4","Ja","Mac OS","Ja","1","ärmlichen Verhältnissen"
|
||||
"2025/01/17 3:11:54 PM MEZ","21","3","Weiblich","Medienwissenschaften","4","Ja","Xiaomi","3","3","Ja","Windows 11","Nein","2","dem normalem Mittelstand"
|
||||
"2025/01/17 3:49:36 PM MEZ","19","3","Weiblich","Medienwissenschaften","3","Ja","Samsung","3","4","Ja","Windows 11","Nein","3","dem normalem Mittelstand"
|
||||
|
27
Projekte.md
Normal file
27
Projekte.md
Normal file
@ -0,0 +1,27 @@
|
||||
# Vortrag
|
||||
- 25 min, **jedes** Gruppenmitglied muss einen Redeanteil haben
|
||||
- Folien mitbringen + Präsentationsrechner
|
||||
- Folien bis Sonntag den 16.02.2025 als pdf in StudIP hochladen (Bennenung: _gruppenname_.pdf)
|
||||
- Falls notwendig (für MeWi nicht) Bestätigungszettel mitbringen
|
||||
|
||||
# Aufgaben
|
||||
- Annahmen genau aufschlüsseln
|
||||
- Hypothesen genau beschreiben
|
||||
- Ergebnisse immer interpretieren & kontextuell Einordnen
|
||||
- Visualisierungen nutzen und zeigen
|
||||
- Nicht den ganzen Code zeigen und Zeile für Zeile durchgehen, die relevanten Stellen im Code herausfiltern und in den Kontext der Analyse setzen
|
||||
|
||||
# Termine
|
||||
|
||||
Jeden Freitag 15-16.30 bis zu den Prüfungstermin ist es im SN22.2 möglich auf Hilfestellung für die Aufgaben zurückzugreifen und dort sich als Gruppe zu treffen.
|
||||
|
||||
Die Reihenfolge der Vorträge wird am Vortragstag bekannt gegeben.
|
||||
## 17.02.2025 10-12h
|
||||
- MeWi 1 - Covid-19
|
||||
- MeWi 3 - Discovery of Handwashing
|
||||
- MeWi 5 - Extramarital Affairs
|
||||
- DiKum - Facebook Data
|
||||
## 18.02.2025 10-12h
|
||||
- MeWi 2 - Covid-19
|
||||
- MeWi 4 - Uber Trips
|
||||
- MeWi 6 - Hochschulstatistik
|
||||
Loading…
Reference in New Issue
Block a user