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ergebnisse_hackathon_repo/team-22/README.md
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ergebnisse_hackathon_repo/team-22/README.md
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# Resultate von Team 22
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## Heatmap für Hashtags
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Das geotag-Notebook arbeitet auf einer von hashtag-geografie1 generierten csv-Datei. Also erst das nochmal durchlaufen lassen.
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Für Eingaben gibt's die erste Zelle.
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## Cop Connections
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Visualisierung der Verbindungsstärke zwischen Polizeiaccounts anhand der Anzahl von Mentions
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1444
ergebnisse_hackathon_repo/team-22/cop_connections.ipynb
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ergebnisse_hackathon_repo/team-22/cop_connections.ipynb
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ergebnisse_hackathon_repo/team-22/cop_link.ipynb
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ergebnisse_hackathon_repo/team-22/cop_link.ipynb
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{
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||||
"cells": [
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||||
{
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||||
"cell_type": "code",
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||||
"execution_count": 40,
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||||
"id": "5eecbeeb",
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||||
"metadata": {},
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||||
"outputs": [],
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||||
"source": [
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||||
"import pandas as pd\n",
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||||
"from tqdm import tqdm # Fortschrittsanzeige für pandas\n",
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||||
"tqdm.pandas()\n",
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||||
"tweet_csv = '../data/copbird_table_tweet.csv'\n",
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"entity_csv = '../data/copbird_table_entity.csv'\n",
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"user_csv = '../data/copbird_table_user.csv'\n",
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"\n",
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"limit = None\n",
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"tweets = pd.read_csv(tweet_csv, nrows=limit)\n",
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"entities = pd.read_csv(entity_csv, nrows=limit)\n",
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"users = pd.read_csv(user_csv, nrows=limit)"
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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": 41,
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"id": "1ad0f35a",
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"metadata": {},
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||||
"outputs": [
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{
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"data": {
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"text/plain": [
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"360008"
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||||
]
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},
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"execution_count": 41,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tweets.size"
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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": 42,
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"id": "c0a49030",
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"metadata": {},
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||||
"outputs": [
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{
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"name": "stderr",
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||||
"output_type": "stream",
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"text": [
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"/usr/local/lib/python3.8/dist-packages/pandas/core/strings/accessor.py:101: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.\n",
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" return func(self, *args, **kwargs)\n"
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]
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||||
},
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||||
{
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||||
"data": {
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||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
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||||
" }\n",
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||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
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||||
" }\n",
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||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
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||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
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||||
" <th></th>\n",
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" <th>id</th>\n",
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" <th>tweet_text</th>\n",
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" <th>created_at</th>\n",
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" <th>user_id</th>\n",
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" <th>like_count</th>\n",
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||||
" <th>retweet_count</th>\n",
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||||
" <th>reply_count</th>\n",
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||||
" <th>quote_count</th>\n",
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" <th>contains</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>1</th>\n",
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" <td>1321023114071969792</td>\n",
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" <td>#Zeugengesucht\\nDie Hintergründe zu dem Tötung...</td>\n",
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" <td>2020-10-27 09:37:08</td>\n",
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" <td>2397974054</td>\n",
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" <td>20.0</td>\n",
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" <td>24.0</td>\n",
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" <td>4.0</td>\n",
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" <td>1.0</td>\n",
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" <td>True</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>1321025127388188673</td>\n",
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" <td>RT @bka: EUROPE´S MOST WANTED – Sexualstraftät...</td>\n",
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" <td>2020-10-27 09:45:08</td>\n",
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" <td>2397974054</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>True</td>\n",
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" </tr>\n",
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||||
" </tbody>\n",
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"</table>\n",
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||||
"</div>"
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],
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"text/plain": [
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" id tweet_text \\\n",
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"1 1321023114071969792 #Zeugengesucht\\nDie Hintergründe zu dem Tötung... \n",
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"2 1321025127388188673 RT @bka: EUROPE´S MOST WANTED – Sexualstraftät... \n",
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"\n",
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" created_at user_id like_count retweet_count reply_count \\\n",
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"1 2020-10-27 09:37:08 2397974054 20.0 24.0 4.0 \n",
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"2 2020-10-27 09:45:08 2397974054 NaN NaN NaN \n",
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"\n",
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" quote_count contains \n",
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"1 1.0 True \n",
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"2 NaN True "
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]
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},
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"execution_count": 42,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tweets[\"contains\"] = tweets[\"tweet_text\"].str.contains(r'(https://t.co/)')\n",
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"tweets_subset = tweets[tweets[\"contains\"]]\n",
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"tweets_link = tweets_subset\n",
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"tweets_link.head(2)"
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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": 43,
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"id": "a5e2d37e",
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||||
"metadata": {},
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||||
"outputs": [
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{
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"name": "stderr",
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||||
"output_type": "stream",
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"text": [
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||||
"<ipython-input-43-393ebe765dff>:1: SettingWithCopyWarning: \n",
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||||
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
|
||||
"Try using .loc[row_indexer,col_indexer] = value instead\n",
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"\n",
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||||
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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" tweets_subset[\"link\"] = tweets_subset[\"tweet_text\"].str.extract(r'(https://t.co/[\\w]*)[\\w$|\\s|\\n][^(.*).{1} ]')\n"
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]
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||||
}
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||||
],
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||||
"source": [
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"tweets_subset[\"link\"] = tweets_subset[\"tweet_text\"].str.extract(r'(https://t.co/[\\w]*)[\\w$|\\s|\\n][^(.*).{1} ]')\n",
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"tryout = tweets_subset\n"
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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": 44,
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"id": "957a6b06",
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"metadata": {},
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"outputs": [],
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"source": [
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"#tryout = tryout.head(9)"
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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": null,
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"id": "b768104e",
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"metadata": {},
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||||
"outputs": [],
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||||
"source": [
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||||
"import io\n",
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"import requests\n",
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"response_arr = []\n",
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"#url = tryout[\"link\"].to_string(index=False)\n",
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"df = pd.DataFrame(data=response_arr, columns=[\"full_link\"])\n",
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"\n",
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"for i in tryout.index:\n",
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" try:\n",
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||||
" response = requests.get(tryout[\"link\"][i])\n",
|
||||
" response_arr.append(response.url)\n",
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" \n",
|
||||
" except:\n",
|
||||
" response_arr.append(\"error\")\n",
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||||
" finally:\n",
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" \n",
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||||
" df = pd.DataFrame([i, response.url], columns=[\"full_link\"])\n",
|
||||
" df.to_csv('links.csv', mode='a', header=False)\n"
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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": 9,
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||||
"id": "1c5f3260",
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||||
"metadata": {},
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||||
"outputs": [
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||||
{
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||||
"ename": "NameError",
|
||||
"evalue": "name 'response_arr' is not defined",
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||||
"output_type": "error",
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||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-9-30722b9a87cd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresponse_arr_orig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse_arr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mtryout\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"link_long\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"nan\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mresponse_arr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mtryout\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"link_long\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'response_arr' is not defined"
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]
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||||
}
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||||
],
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"source": [
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"response_arr_orig = response_arr\n",
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"tryout[\"link_long\"]=float(\"nan\")\n",
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"index = 0\n",
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"for i in response_arr:\n",
|
||||
" tryout[\"link_long\"][index]=i\n",
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" index = index+1\n",
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||||
"print(index)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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ergebnisse_hackathon_repo/team-22/geolikes.ipynb
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ergebnisse_hackathon_repo/team-22/geolikes.ipynb
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ergebnisse_hackathon_repo/team-22/geotags.ipynb
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ergebnisse_hackathon_repo/team-22/geotags.ipynb
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ergebnisse_hackathon_repo/team-22/hashtag-geografie1.ipynb
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ergebnisse_hackathon_repo/team-22/hashtag-geografie1.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "847f9651",
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"metadata": {},
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"source": [
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"Pakete laden"
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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": "0a01b63b",
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"metadata": {},
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||||
"outputs": [],
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"source": [
|
||||
"import pandas as pd\n",
|
||||
"from tqdm import tqdm # Fortschrittsanzeige für pandas\n",
|
||||
"tqdm.pandas()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b515c823",
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||||
"metadata": {},
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||||
"source": [
|
||||
"Daten laden"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
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||||
"id": "0eec2734",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"tweet_csv = '../data/copbird_table_tweet.csv'\n",
|
||||
"entity_csv = '../data/copbird_table_entity.csv'\n",
|
||||
"user_csv = '../data/copbird_table_user.csv'\n",
|
||||
"cop_geolocations_csv = '../geolocations/polizei_accounts_geo.csv'"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
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||||
"id": "fbe080bc",
|
||||
"metadata": {},
|
||||
"outputs": [],
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||||
"source": [
|
||||
"limit = None\n",
|
||||
"tweets = pd.read_csv(tweet_csv, nrows=limit)\n",
|
||||
"entities = pd.read_csv(entity_csv, nrows=limit)\n",
|
||||
"users = pd.read_csv(user_csv, nrows=limit)\n",
|
||||
"geolocs = pd.read_csv(cop_geolocations_csv, sep=r'\\t', engine='python', nrows=limit)\n",
|
||||
"# skip first two rows since they do not contain GPS data\n",
|
||||
"geolocs = geolocs.iloc[2:, :]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "b4e5b2b7",
|
||||
"metadata": {},
|
||||
"outputs": [
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{
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"data": {
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||||
"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>tweet_id</th>\n",
|
||||
" <th>tag</th>\n",
|
||||
" <th>entity_type</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>18</th>\n",
|
||||
" <td>1321050580337512448</td>\n",
|
||||
" <td>Alsdorf</td>\n",
|
||||
" <td>hashtag</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>20</th>\n",
|
||||
" <td>1321050612142870534</td>\n",
|
||||
" <td>Frankfurt</td>\n",
|
||||
" <td>hashtag</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>21</th>\n",
|
||||
" <td>1321050612142870534</td>\n",
|
||||
" <td>A3</td>\n",
|
||||
" <td>hashtag</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>22</th>\n",
|
||||
" <td>1321050732917829639</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>hashtag</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>23</th>\n",
|
||||
" <td>1321050732917829639</td>\n",
|
||||
" <td>Aachen</td>\n",
|
||||
" <td>hashtag</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" tweet_id tag entity_type\n",
|
||||
"18 1321050580337512448 Alsdorf hashtag\n",
|
||||
"20 1321050612142870534 Frankfurt hashtag\n",
|
||||
"21 1321050612142870534 A3 hashtag\n",
|
||||
"22 1321050732917829639 Polizei hashtag\n",
|
||||
"23 1321050732917829639 Aachen hashtag"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"hashtags = entities[entities['entity_type'] == 'hashtag']\n",
|
||||
"hashtags.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "8c426c02",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Häufigkeit von Tweets mit GPS-Stempel"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "b70fd2b2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
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|
||||
" vertical-align: middle;\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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|
||||
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|
||||
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|
||||
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|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>tweet_id</th>\n",
|
||||
" <th>user_id</th>\n",
|
||||
" <th>tag</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>1321050580337512448</td>\n",
|
||||
" <td>2389142300</td>\n",
|
||||
" <td>Alsdorf</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>1321050612142870534</td>\n",
|
||||
" <td>2272909014</td>\n",
|
||||
" <td>Frankfurt</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>1321050612142870534</td>\n",
|
||||
" <td>2272909014</td>\n",
|
||||
" <td>A3</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>1321050732917829639</td>\n",
|
||||
" <td>2389142300</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>1321050732917829639</td>\n",
|
||||
" <td>2389142300</td>\n",
|
||||
" <td>Aachen</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" tweet_id user_id tag\n",
|
||||
"0 1321050580337512448 2389142300 Alsdorf\n",
|
||||
"1 1321050612142870534 2272909014 Frankfurt\n",
|
||||
"2 1321050612142870534 2272909014 A3\n",
|
||||
"3 1321050732917829639 2389142300 Polizei\n",
|
||||
"4 1321050732917829639 2389142300 Aachen"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Füge den Accounts, zu denen es ein GPS-Datum gibt, dieses hinzu:\n",
|
||||
"users['handle'] = users['handle'].str.lower().str.strip()\n",
|
||||
"geolocs['Polizei Account'] = geolocs['Polizei Account'].str.lower().str.strip()\n",
|
||||
"users_geolocs = users.merge(geolocs, left_on='handle', right_on='Polizei Account', how='inner')\n",
|
||||
"# Die Spalte mit dem Handle brauchen wir nur einmal:\n",
|
||||
"users_geolocs.drop(columns='Polizei Account', inplace=True)\n",
|
||||
"# Füge dazu, falls vorhanden, Tweets hinzu:\n",
|
||||
"#us_ge_tw = users_geolocs.merge(tweets, left_on='id', right_on='user_id', how='inner')\n",
|
||||
"# Wieder redundante Spalte wegschmeißen:\n",
|
||||
"#us_ge_tw.drop(columns='id_x', inplace=True)\n",
|
||||
"#us_ge_tw.rename(columns={'id_y':'id'}, inplace=True)\n",
|
||||
"#us_ge_tw.head()\n",
|
||||
"# Füge Hashtags dazu\n",
|
||||
"tw_ht = tweets.merge(hashtags, left_on='id', right_on='tweet_id', how='inner')[['tweet_id','user_id','tag']]\n",
|
||||
"tw_ht.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2c36168a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Hashtags zusammenfassen:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "4d8c367d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>user_id</th>\n",
|
||||
" <th>tag</th>\n",
|
||||
" <th>count</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>549</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>632</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>551</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Leverkusen</td>\n",
|
||||
" <td>630</td>\n",
|
||||
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|
||||
" <tr>\n",
|
||||
" <th>565</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>PolizeiNRW</td>\n",
|
||||
" <td>630</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>19658</th>\n",
|
||||
" <td>808666671468658688</td>\n",
|
||||
" <td>Bremen</td>\n",
|
||||
" <td>445</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>19737</th>\n",
|
||||
" <td>808666671468658688</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>427</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" user_id tag count\n",
|
||||
"549 259607457 Köln 632\n",
|
||||
"551 259607457 Leverkusen 630\n",
|
||||
"565 259607457 PolizeiNRW 630\n",
|
||||
"19658 808666671468658688 Bremen 445\n",
|
||||
"19737 808666671468658688 Polizei 427"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"ht_count = tw_ht.groupby(['user_id','tag']).size().reset_index(name='count').sort_values(by='count', ascending=False)\n",
|
||||
"ht_count.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "2bfaaeec",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
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|
||||
"<style scoped>\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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>user_id</th>\n",
|
||||
" <th>tag</th>\n",
|
||||
" <th>count</th>\n",
|
||||
" <th>handle</th>\n",
|
||||
" <th>Name</th>\n",
|
||||
" <th>Typ</th>\n",
|
||||
" <th>Bundesland</th>\n",
|
||||
" <th>Stadt</th>\n",
|
||||
" <th>LAT</th>\n",
|
||||
" <th>LONG</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>632</td>\n",
|
||||
" <td>polizei_nrw_k</td>\n",
|
||||
" <td>Polizei NRW K</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>Nordrhein-Westfalen</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>50.938361</td>\n",
|
||||
" <td>6.959974</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Leverkusen</td>\n",
|
||||
" <td>630</td>\n",
|
||||
" <td>polizei_nrw_k</td>\n",
|
||||
" <td>Polizei NRW K</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>Nordrhein-Westfalen</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>50.938361</td>\n",
|
||||
" <td>6.959974</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>PolizeiNRW</td>\n",
|
||||
" <td>630</td>\n",
|
||||
" <td>polizei_nrw_k</td>\n",
|
||||
" <td>Polizei NRW K</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>Nordrhein-Westfalen</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>50.938361</td>\n",
|
||||
" <td>6.959974</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Zeugensuche</td>\n",
|
||||
" <td>32</td>\n",
|
||||
" <td>polizei_nrw_k</td>\n",
|
||||
" <td>Polizei NRW K</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>Nordrhein-Westfalen</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>50.938361</td>\n",
|
||||
" <td>6.959974</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>259607457</td>\n",
|
||||
" <td>Einbruchradar</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>polizei_nrw_k</td>\n",
|
||||
" <td>Polizei NRW K</td>\n",
|
||||
" <td>Polizei</td>\n",
|
||||
" <td>Nordrhein-Westfalen</td>\n",
|
||||
" <td>Köln</td>\n",
|
||||
" <td>50.938361</td>\n",
|
||||
" <td>6.959974</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" user_id tag count handle Name Typ \\\n",
|
||||
"0 259607457 Köln 632 polizei_nrw_k Polizei NRW K Polizei \n",
|
||||
"1 259607457 Leverkusen 630 polizei_nrw_k Polizei NRW K Polizei \n",
|
||||
"2 259607457 PolizeiNRW 630 polizei_nrw_k Polizei NRW K Polizei \n",
|
||||
"3 259607457 Zeugensuche 32 polizei_nrw_k Polizei NRW K Polizei \n",
|
||||
"4 259607457 Einbruchradar 21 polizei_nrw_k Polizei NRW K Polizei \n",
|
||||
"\n",
|
||||
" Bundesland Stadt LAT LONG \n",
|
||||
"0 Nordrhein-Westfalen Köln 50.938361 6.959974 \n",
|
||||
"1 Nordrhein-Westfalen Köln 50.938361 6.959974 \n",
|
||||
"2 Nordrhein-Westfalen Köln 50.938361 6.959974 \n",
|
||||
"3 Nordrhein-Westfalen Köln 50.938361 6.959974 \n",
|
||||
"4 Nordrhein-Westfalen Köln 50.938361 6.959974 "
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"ht_geo = ht_count.merge(users_geolocs, left_on=\"user_id\", right_on=\"id\", how=\"inner\")\n",
|
||||
"ht_geo.drop(columns=['name','id'], inplace=True)\n",
|
||||
"ht_geo.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "3db0daf3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"ht_geo.to_csv(\"hashtags_users_geolocs.csv\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
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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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|
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|
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|
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|
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|
||||
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|
||||
"nbformat_minor": 5
|
||||
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|
||||
|
|
@ -0,0 +1,70 @@
|
|||
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|
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|
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|
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|
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{"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
||||
).addTo(map_ebe45c1fb4d04d1a95be4f62657f738b);
|
||||
|
||||
|
||||
var heat_map_e73488534b334eda9b44e979b66e7054 = L.heatLayer(
|
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[[51.4818111, 7.2196635, 1.0], [49.234362, 6.996379, 1.0], [51.842828, 12.230393, 2.0], [52.1315889, 11.6399609, 2.0], [51.264018, 7.1780374, 1.0], [48.3974003, 9.9934336, 2.0], [48.8819801, 12.569716, 1.0], [50.769478, 7.187579, 1.0], [52.520007, 13.404954, 1.0], [52.6050782, 11.8594279, 2.0], [51.4825041, 11.9705452, 1.0], [52.390569, 13.064473, 2.0], [52.266837, 8.049741, 2.0], [51.828835, 9.4466591, 2.0], [52.1503721, 10.3593147, 1.0], [47.8539273, 12.127262, 1.0]],
|
||||
{"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
|
||||
).addTo(map_ebe45c1fb4d04d1a95be4f62657f738b);
|
||||
|
||||
</script>
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
|
||||
|
||||
<script>
|
||||
L_NO_TOUCH = false;
|
||||
L_DISABLE_3D = false;
|
||||
</script>
|
||||
|
||||
<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
|
||||
<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
|
||||
<script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
|
||||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
|
||||
|
||||
<meta name="viewport" content="width=device-width,
|
||||
initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
|
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<style>
|
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#map_5a06192c8dc849ebb51e1684eec6a072 {
|
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position: relative;
|
||||
width: 100.0%;
|
||||
height: 100.0%;
|
||||
left: 0.0%;
|
||||
top: 0.0%;
|
||||
}
|
||||
</style>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<div class="folium-map" id="map_5a06192c8dc849ebb51e1684eec6a072" ></div>
|
||||
|
||||
</body>
|
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<script>
|
||||
|
||||
var map_5a06192c8dc849ebb51e1684eec6a072 = L.map(
|
||||
"map_5a06192c8dc849ebb51e1684eec6a072",
|
||||
{
|
||||
center: [51.423, 9.03],
|
||||
crs: L.CRS.EPSG3857,
|
||||
zoom: 6,
|
||||
zoomControl: true,
|
||||
preferCanvas: false,
|
||||
}
|
||||
);
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
var tile_layer_8aad6cc72e2246d081b995f6aa6913b8 = L.tileLayer(
|
||||
"https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
|
||||
{"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
||||
).addTo(map_5a06192c8dc849ebb51e1684eec6a072);
|
||||
|
||||
|
||||
var heat_map_f290006b43454c8d8b8c27f866e81e39 = L.heatLayer(
|
||||
[],
|
||||
{"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
|
||||
).addTo(map_5a06192c8dc849ebb51e1684eec6a072);
|
||||
|
||||
</script>
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
|
||||
|
||||
<script>
|
||||
L_NO_TOUCH = false;
|
||||
L_DISABLE_3D = false;
|
||||
</script>
|
||||
|
||||
<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
|
||||
<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
|
||||
<script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
|
||||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
|
||||
|
||||
<meta name="viewport" content="width=device-width,
|
||||
initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
|
||||
<style>
|
||||
#map_f04a5cf204f8442da011a485ac471876 {
|
||||
position: relative;
|
||||
width: 100.0%;
|
||||
height: 100.0%;
|
||||
left: 0.0%;
|
||||
top: 0.0%;
|
||||
}
|
||||
</style>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<div class="folium-map" id="map_f04a5cf204f8442da011a485ac471876" ></div>
|
||||
|
||||
</body>
|
||||
<script>
|
||||
|
||||
var map_f04a5cf204f8442da011a485ac471876 = L.map(
|
||||
"map_f04a5cf204f8442da011a485ac471876",
|
||||
{
|
||||
center: [51.423, 9.03],
|
||||
crs: L.CRS.EPSG3857,
|
||||
zoom: 6,
|
||||
zoomControl: true,
|
||||
preferCanvas: false,
|
||||
}
|
||||
);
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
var tile_layer_120a2f57890243ce9409df877e47e282 = L.tileLayer(
|
||||
"https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
|
||||
{"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
||||
).addTo(map_f04a5cf204f8442da011a485ac471876);
|
||||
|
||||
|
||||
var heat_map_8abdc313946b4aa5a79ec29dff1e1d3d = L.heatLayer(
|
||||
[],
|
||||
{"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
|
||||
).addTo(map_f04a5cf204f8442da011a485ac471876);
|
||||
|
||||
</script>
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
|
||||
|
||||
<script>
|
||||
L_NO_TOUCH = false;
|
||||
L_DISABLE_3D = false;
|
||||
</script>
|
||||
|
||||
<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
|
||||
<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
|
||||
<script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
|
||||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
|
||||
|
||||
<meta name="viewport" content="width=device-width,
|
||||
initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
|
||||
<style>
|
||||
#map_a08fa9b693bf4a5a815962b957e44fc4 {
|
||||
position: relative;
|
||||
width: 100.0%;
|
||||
height: 100.0%;
|
||||
left: 0.0%;
|
||||
top: 0.0%;
|
||||
}
|
||||
</style>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<div class="folium-map" id="map_a08fa9b693bf4a5a815962b957e44fc4" ></div>
|
||||
|
||||
</body>
|
||||
<script>
|
||||
|
||||
var map_a08fa9b693bf4a5a815962b957e44fc4 = L.map(
|
||||
"map_a08fa9b693bf4a5a815962b957e44fc4",
|
||||
{
|
||||
center: [51.423, 9.03],
|
||||
crs: L.CRS.EPSG3857,
|
||||
zoom: 6,
|
||||
zoomControl: true,
|
||||
preferCanvas: false,
|
||||
}
|
||||
);
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
var tile_layer_9ab2306557eb41e9be1c098bbf5d6784 = L.tileLayer(
|
||||
"https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
|
||||
{"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
||||
).addTo(map_a08fa9b693bf4a5a815962b957e44fc4);
|
||||
|
||||
|
||||
var heat_map_f4c5c6980dcb4c3cb537fa8a08f9b7a2 = L.heatLayer(
|
||||
[[47.999008, 7.842104, 6.0]],
|
||||
{"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
|
||||
).addTo(map_a08fa9b693bf4a5a815962b957e44fc4);
|
||||
|
||||
</script>
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
|
||||
|
||||
<script>
|
||||
L_NO_TOUCH = false;
|
||||
L_DISABLE_3D = false;
|
||||
</script>
|
||||
|
||||
<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
|
||||
<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
|
||||
<script src="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js"></script>
|
||||
<script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
|
||||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
|
||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
|
||||
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
|
||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
|
||||
|
||||
<meta name="viewport" content="width=device-width,
|
||||
initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
|
||||
<style>
|
||||
#map_c83da2fa6eea4f18b3c984ff31f38da7 {
|
||||
position: relative;
|
||||
width: 100.0%;
|
||||
height: 100.0%;
|
||||
left: 0.0%;
|
||||
top: 0.0%;
|
||||
}
|
||||
</style>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/gh/python-visualization/folium@master/folium/templates/leaflet_heat.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
<div class="folium-map" id="map_c83da2fa6eea4f18b3c984ff31f38da7" ></div>
|
||||
|
||||
</body>
|
||||
<script>
|
||||
|
||||
var map_c83da2fa6eea4f18b3c984ff31f38da7 = L.map(
|
||||
"map_c83da2fa6eea4f18b3c984ff31f38da7",
|
||||
{
|
||||
center: [51.423, 9.03],
|
||||
crs: L.CRS.EPSG3857,
|
||||
zoom: 6,
|
||||
zoomControl: true,
|
||||
preferCanvas: false,
|
||||
}
|
||||
);
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
var tile_layer_bfc9ad4d67cc457b9786cf80eb52a7a8 = L.tileLayer(
|
||||
"https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
|
||||
{"attribution": "Data by \u0026copy; \u003ca href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
||||
).addTo(map_c83da2fa6eea4f18b3c984ff31f38da7);
|
||||
|
||||
|
||||
var heat_map_549f5561514c459d8ac2fa173de6c52d = L.heatLayer(
|
||||
[],
|
||||
{"blur": 15, "maxZoom": 18, "minOpacity": 0.5, "radius": 25}
|
||||
).addTo(map_c83da2fa6eea4f18b3c984ff31f38da7);
|
||||
|
||||
</script>
|
||||
Loading…
Add table
Add a link
Reference in a new issue