Changed: Projects
This commit is contained in:
@@ -1180,7 +1180,7 @@
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"name": "python",
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"version": "3.8.16"
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@@ -2,662 +2,247 @@
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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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"- Excerzises a bit more complicated"
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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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]
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{
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"cell_type": "markdown",
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"id": "8b43eadd-f8a2-44fa-bb87-1f0c6ecc32b2",
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"metadata": {},
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"metadata": {
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}
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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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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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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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]
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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"id": "489e967c-b75b-42d4-b479-f8ca1a9e585b",
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"cell_type": "markdown",
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}
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},
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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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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "0e941e01-268d-40c3-82dc-7c02ea9bbfd4",
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"metadata": {
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"tags": []
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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"\n",
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" .dataframe tbody tr th {\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Page total likes</th>\n",
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" <th>Type</th>\n",
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" <th>Category</th>\n",
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" <th>Post Month</th>\n",
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" <th>Post Weekday</th>\n",
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" <th>Post Hour</th>\n",
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" <th>Paid</th>\n",
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" <th>Lifetime Post Total Reach</th>\n",
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" <th>Lifetime Post Total Impressions</th>\n",
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" <th>Lifetime Engaged Users</th>\n",
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" <th>Lifetime Post Consumers</th>\n",
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" <th>Lifetime Post Consumptions</th>\n",
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" <th>Lifetime Post Impressions by people who have liked your Page</th>\n",
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" <th>Lifetime Post reach by people who like your Page</th>\n",
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" <th>Lifetime People who have liked your Page and engaged with your post</th>\n",
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" <th>comment</th>\n",
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" <th>like</th>\n",
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" <th>share</th>\n",
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" <th>Total Interactions</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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||||
" <th>0</th>\n",
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||||
" <td>139441</td>\n",
|
||||
" <td>Photo</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>12</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>3</td>\n",
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||||
" <td>0.0</td>\n",
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||||
" <td>2752</td>\n",
|
||||
" <td>5091</td>\n",
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||||
" <td>178</td>\n",
|
||||
" <td>109</td>\n",
|
||||
" <td>159</td>\n",
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||||
" <td>3078</td>\n",
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||||
" <td>1640</td>\n",
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||||
" <td>119</td>\n",
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||||
" <td>4</td>\n",
|
||||
" <td>79.0</td>\n",
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||||
" <td>17.0</td>\n",
|
||||
" <td>100</td>\n",
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||||
" </tr>\n",
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" <tr>\n",
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||||
" <th>1</th>\n",
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||||
" <td>139441</td>\n",
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||||
" <td>Status</td>\n",
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||||
" <td>2</td>\n",
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||||
" <td>12</td>\n",
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||||
" <td>3</td>\n",
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||||
" <td>10</td>\n",
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||||
" <td>0.0</td>\n",
|
||||
" <td>10460</td>\n",
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||||
" <td>19057</td>\n",
|
||||
" <td>1457</td>\n",
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||||
" <td>1361</td>\n",
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||||
" <td>1674</td>\n",
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||||
" <td>11710</td>\n",
|
||||
" <td>6112</td>\n",
|
||||
" <td>1108</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>130.0</td>\n",
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||||
" <td>29.0</td>\n",
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||||
" <td>164</td>\n",
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||||
" </tr>\n",
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" <tr>\n",
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||||
" <th>2</th>\n",
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||||
" <td>139441</td>\n",
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||||
" <td>Photo</td>\n",
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||||
" <td>3</td>\n",
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||||
" <td>12</td>\n",
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||||
" <td>3</td>\n",
|
||||
" <td>3</td>\n",
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||||
" <td>0.0</td>\n",
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||||
" <td>2413</td>\n",
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||||
" <td>4373</td>\n",
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||||
" <td>177</td>\n",
|
||||
" <td>113</td>\n",
|
||||
" <td>154</td>\n",
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||||
" <td>2812</td>\n",
|
||||
" <td>1503</td>\n",
|
||||
" <td>132</td>\n",
|
||||
" <td>0</td>\n",
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||||
" <td>66.0</td>\n",
|
||||
" <td>14.0</td>\n",
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||||
" <td>80</td>\n",
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||||
" </tr>\n",
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" <tr>\n",
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||||
" <th>3</th>\n",
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||||
" <td>139441</td>\n",
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||||
" <td>Photo</td>\n",
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||||
" <td>2</td>\n",
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||||
" <td>12</td>\n",
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||||
" <td>2</td>\n",
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||||
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||||
" <td>1.0</td>\n",
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||||
" <td>50128</td>\n",
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||||
" <td>87991</td>\n",
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||||
" <td>2211</td>\n",
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||||
" <td>790</td>\n",
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||||
" <td>1119</td>\n",
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||||
" <td>61027</td>\n",
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||||
" <td>32048</td>\n",
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||||
" <td>1386</td>\n",
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||||
" <td>58</td>\n",
|
||||
" <td>1572.0</td>\n",
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||||
" <td>147.0</td>\n",
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||||
" <td>1777</td>\n",
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||||
" </tr>\n",
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" <tr>\n",
|
||||
" <th>4</th>\n",
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||||
" <td>139441</td>\n",
|
||||
" <td>Photo</td>\n",
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||||
" <td>2</td>\n",
|
||||
" <td>12</td>\n",
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||||
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|
||||
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||||
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||||
" <td>7244</td>\n",
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||||
" <td>13594</td>\n",
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||||
" <td>671</td>\n",
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||||
" <td>410</td>\n",
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||||
" <td>580</td>\n",
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||||
" <td>6228</td>\n",
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||||
" <td>3200</td>\n",
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||||
" <td>396</td>\n",
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||||
" <td>19</td>\n",
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||||
" <td>325.0</td>\n",
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||||
" <td>49.0</td>\n",
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||||
" <td>393</td>\n",
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||||
" <th>...</th>\n",
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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" <tr>\n",
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||||
" <th>495</th>\n",
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||||
" <td>85093</td>\n",
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" <td>Photo</td>\n",
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" <td>3</td>\n",
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||||
" <td>1</td>\n",
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||||
" <td>7</td>\n",
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||||
" <td>2</td>\n",
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||||
" <td>0.0</td>\n",
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||||
" <td>4684</td>\n",
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||||
" <td>7536</td>\n",
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||||
" <td>733</td>\n",
|
||||
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|
||||
" <td>985</td>\n",
|
||||
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|
||||
" <td>2876</td>\n",
|
||||
" <td>392</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>53.0</td>\n",
|
||||
" <td>26.0</td>\n",
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||||
" <td>84</td>\n",
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" </tr>\n",
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" <tr>\n",
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||||
" <th>496</th>\n",
|
||||
" <td>81370</td>\n",
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||||
" <td>Photo</td>\n",
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||||
" <td>2</td>\n",
|
||||
" <td>1</td>\n",
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||||
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|
||||
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|
||||
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|
||||
" <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",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <td>7216</td>\n",
|
||||
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|
||||
" <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",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <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",
|
||||
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|
||||
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|
||||
" <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",
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||||
"</div>"
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||||
],
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"text/plain": [
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||||
" 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",
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||||
".. ... ... ... ... ... ... \n",
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||||
"495 85093 Photo 3 1 7 2 \n",
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||||
"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,
|
||||
|
||||
Reference in New Issue
Block a user