How to plot a pie chart with four column in the dataset by using Plotly in python

Question

Dataset:

Year      ,    Store_type   ,      MY_SHOPPING         ,TRAN_SPEND
2012,      LARGE_STORE  ,         HEALTH CONSCIOUS  ,    49383.70$
2012  ,   CONVENIENCE_STORE  ,   CONFIDENT COOKS      ,  13150.00$
2013  , LARGER_STORE        ,   QUICK&EASY        ,  98765.00$
2013  , LARGER_STORE      ,    TRADITIONAL        ,  45734.00$

Question: I want to have a pie chart that represents the year in the middle of the chart and have a label = store_type and display percentage of different categories in MY_SHOPPING column plus the name of that and also the TRAN_SPEND amount in dollar

.

My code:

fig = px.pie(removed_index_storeformat, values='TRAN_SPEND', names='STORE_TYPE',
             hover_data=['MY_SHOPPING '], labels={'MY_SHOPPING ':'shop'})

fig.update_traces(textposition='inside', textinfo='percent+label')
fig.show()

Answer 1

Donut pie charts are made possible by setting the hole size. Also, use annotations to put text strings inside the Add a numerical column separate from the column of strings marked with dollar signs in the data presented. Use the numerical column for the pie chart and the original dollar-marked column for the text.

import pandas as pd
import numpy as np
import io

data = '''
Year,Store_type,MY_SHOPPING,TRAN_SPEND
2012,LARGE_STORE,HEALTH CONSCIOUS,49383.70$
2012,CONVENIENCE_STORE,CONFIDENT COOKS,13150.00$
2013,LARGER_STORE,QUICK&EASY,98765.00$
2013,LARGER_STORE,TRADITIONAL,45734.00$
'''

df = pd.read_csv(io.StringIO(data), sep=',')

df['TRAN_SPEND2'] = df['TRAN_SPEND'].apply(lambda x: float(x[:-1]))
df

    Year    Store_type  MY_SHOPPING     TRAN_SPEND  TRAN_SPEND2
0   2012    LARGE_STORE     HEALTH CONSCIOUS    49383.70$   49383.7
1   2012    CONVENIENCE_STORE   CONFIDENT COOKS     13150.00$   13150.0
2   2013    LARGER_STORE    QUICK&EASY  98765.00$   98765.0
3   2013    LARGER_STORE    TRADITIONAL     45734.00$   45734.0


import plotly.express as px

dff = df.query('Year == 2012')
fig = px.pie(dff, values='TRAN_SPEND2', names='Store_type',
             hover_data=['MY_SHOPPING'], labels={'MY_SHOPPING ':'shop'}, hole=0.3)

fig.update_traces(textposition='inside', text=dff['TRAN_SPEND'], textinfo='percent+label+text')

fig.update_layout(
    title_text="Test Title",
    annotations=[dict(text='2012', x=0.5, y=0.5, font_size=20, showarrow=False)])

fig.show()