KeiraSummerCode/lookpie at master · getzlab/KeiraSummerCode · GitHub

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import plotly.express as px
import plotly.graph_objects as go
import plotly.io as pio
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
import pandas as pd
import matplotlib.patches as mpatches
import matplotlib.colors as mpcolor
import matplotlib.cm as cm
from matplotlib.lines import Line2D
import math
import plotly.graph_objects as go
from plotly.subplots import make_subplots

df = pd.read_csv('Juric_Rapid_Autopsy_MASTER-treatments1.csv', sep=',')
df2=pd.read_csv('Juric_Rapid_Autopsy_MASTER-participants.txt', sep='\t')
df=pd.merge(df,df2, on='participant_id', how='inner')


genderlabels=df['gender'].unique().tolist()
gendervalues = df['gender'].value_counts().tolist()

racelabels=df['race'].unique().tolist()
racevalues = df['race'].value_counts().tolist()

vitallabels=df['vital_status'].unique().tolist()
vitalvalues = df['vital_status'].value_counts().tolist()

catlabels=df['categories'].unique().tolist()
catvalues=df['categories'].value_counts().tolist()

fig =make_subplots(rows=2, cols=2, specs=[[{'type':'domain'}, {'type':'domain'}],[{'type':'domain'},{'type':'domain'}]])

fig.add_trace(go.Pie(labels=genderlabels, values=gendervalues, name="Gender"),
              1, 1)
fig.add_trace(go.Pie(labels=racelabels, values=racevalues, name="Race"),
              1, 2)
fig.add_trace(go.Pie(labels=vitallabels, values=vitalvalues, name="Vitals"),
              2, 1)
fig.add_trace(go.Pie(labels=catlabels, values=catvalues, name="Cat"),
              2, 2)


fig.update_traces(hole=.4, hoverinfo="label+percent+name")

fig.update_layout(
    title_text="Demographic Distributions",
    annotations=[dict(text='Gender', x=0.225, y=0.83,
                      font_size=15, showarrow=False, xanchor="center"),
                 dict(text='Race', x=0.775, y=0.83,
                      font_size=15, showarrow=False, xanchor="center"),
                 dict(text='Status', x=0.225, y=0.21,
                      font_size=15, showarrow=False, xanchor="center"),
                 dict(text='Category', x=0.775, y=0.21,
                      font_size=15, showarrow=False, xanchor="center")],
    showlegend=False)
fig.write_html('newpieplot.html')