map_schatzmeister.py

# -*- coding: utf-8 -*-
"""map_schatzmeister.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1ztBOPXSu-SK5Ykp1TRo4iuzsM5SoW5mA
"""

# Quelle: https://colab.research.google.com/drive/19TbFZCaOBcCJ8aNoRM0CAfhAZqDnPaVm#scrollTo=bMnYdhHoTDcU
# Quelle2: https://python-graph-gallery.com/313-bubble-map-with-folium/
# import and install packages
!pip install geopy # geocoding library
!pip install folium
import folium
import pandas as pd
from geopy.geocoders import Nominatim

# create a geocoder that uses OpenStreetMap Nominatim API
geolocator = Nominatim(timeout=10, user_agent = "dlab.berkeley.edu-workshop")

# read data
df = pd.read_csv('ergebnis_28082020_loesch_ohne_duplikate.csv', sep = ";")
df

# add the column "Anzahl"
df['anzahl'] = 1
df

!ls

# number of gifts by postcode
df_pivot = df.pivot_table(values='anzahl', index='postleitzahl', aggfunc='sum')
df_pivot.reset_index(inplace=True)
df_pivot

# geocode the addresses in the pandas df
# Iterates over all rows in the dataframe df.
# Joins the values in the columns Landmark, City, and State into one string (the full address)
# Submits the string we just created as the address to be geocoded
# Saves results to the geocodes list object.
geocodes = [geolocator.geocode({'country': 'de', 'postalcode': df_pivot.loc[i, 'postleitzahl']}) for i in range(len(df_pivot))]
geocodes

# add parts of the output latitude and longitude values in the geocodes list to the df dataframe
df_pivot['lat'] = [g.latitude for g in geocodes]
df_pivot['lon'] = [g.longitude for g in geocodes]
df_pivot

# first make an empty map centered on Münster
map1 = folium.Map(location=(51.9606649,	7.6261347), zoom_start=12)
for index,row in df_pivot.iterrows(): 
  # Add the geocoded locations to the map
  folium.Marker([row['lat'],row['lon']], popup=str(int(row['anzahl']))).add_to(map1)

display(map1)

# save the map
map1.save("muenster_marker.html")

# first make an empty map centered on Münster
map2 = folium.Map(location=(51.9606649,	7.6261347), zoom_start=11.5)
for index,row in df_pivot.iterrows(): 
  # Add the geocoded locations to the map
  folium.Circle([row['lat'],row['lon']], 
                popup=str(int(row['anzahl'])), 
                radius=row['anzahl']*4, 
                fill=True, 
                fill_color='blue').add_to(map2)

display(map2)

# save the map
map2.save("muenster_bubble.html")