vasoAuthorGraphs.py

#!/usr/bin/python
import pandas as pd
import matplotlib.pyplot as plt
from collections import Counter

sheet_id = '1REpJa7gl4i7Dxbw-JHcF-dhne3UFgqwkKE_If1nXrmY'
sheet_name = 'Included'
url = f'https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv&sheet={sheet_name}'
data = pd.read_csv(url).sort_values(by=['Count','First Author'])

# Pie chart
plt.style.use('fivethirtyeight')

backgroundCounter = Counter()
for i, row in data.iterrows():
    backgroundCounter.update([row['Background']])

backgrounds = []
counts = []

for key in backgroundCounter:
    if key == 'unknown':
        continue
    backgrounds.append(key)
    counts.append(backgroundCounter[key])

pieData = pd.DataFrame({'backgrounds':backgrounds, 'counts':counts})
pieData = pieData.sort_values(by=['counts'], ascending=False)

# colors generated here:
# https://learnui.design/tools/data-color-picker.html#palette
colors = ['#003f5c','#374c80','#7a5195','#bc5090','#ef5675','#ff764a','#ffa600']
plt.pie(pieData['counts'], labels=pieData['backgrounds'], counterclock=False,colors=colors,startangle=-270)
plt.title("Backgrounds of First Authors of VASO Layer-fMRI Papers in Humans")
plt.savefig('vasoAuthorsPie.png',bbox_inches='tight')
plt.show()



# horizontal bar chart

plt.barh(data['First Author'], data['Count'], color='#003f5c')
plt.title('Number of First Author Human Layer fMRI Papers using VASO')
plt.yticks(fontsize=10)

plt.tight_layout()
plt.savefig('vasoAuthorsBar.png',bbox_inches='tight')
plt.show()