<jupyter_start><jupyter_text>Heatmap of top 100 cites in <NAME>  25/07/2018<jupyter_code>import gmaps
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import csv

gmaps.configure(api_key="API") # Personal info, need your Google API key
results=[]
# put locations_top_100_cites.csv in the same dic
with open("locations_top_100_cites.csv") as csvfile: # data of locations of top 100 cites
    reader = csv.reader(csvfile, quoting=csv.QUOTE_NONNUMERIC) # change contents to floats
    for row in reader: # each row is a list
        results.append(row)
# change the list to array
data=np.array(results)
locations = data
#print(locations)
#plt.xkcd()
#gmaps.figure(map_type='HYBRID')

fig=gmaps.figure(layout={
        'width': '700px',
        'height': '500px',
        'padding': '3px',
        'border': '1px solid black'
})
fig.add_layer(gmaps.heatmap_layer(locations))
fig<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11231101511879049, 'fraction_numerical': 0.03023758099352052, 'mean_word_length': 4.618181818181818, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '667183', 'license': 'Apache-2.0', 'n_tokens_mistral': 351, 'n_tokens_neox': 316, 'n_words': 90, 'path': 'Heatmap_of _top_100_cites_in_Vermont.ipynb', 'repo_name': 'kewangchen/Heatmap_of_cites_in_VT', 'size': '939'}