In titanic dataset, I need to create a chart that shows the percentage of passengers for all class who survived. Also it should have three pie charts. class 1 survived and not-survived, class 2 survived and not-survived, class 3.

How can make this happen? I already tried this type of code but it produces wrong values.

import pandas as pd
import seaborn as sns  # for dataset

df_titanic = sns.load_dataset('titanic')

   survived  pclass     sex   age  sibsp  parch     fare embarked  class    who  adult_male deck  embark_town alive  alone
0         0       3    male  22.0      1      0   7.2500        S  Third    man        True  NaN  Southampton    no  False
1         1       1  female  38.0      1      0  71.2833        C  First  woman       False    C    Cherbourg   yes  False
2         1       3  female  26.0      0      0   7.9250        S  Third  woman       False  NaN  Southampton   yes   True

c1s = len(df_titanic[(df_titanic.pclass==1) & (df_titanic.survived==1)].value_counts())
c2ns = len(df_titanic[(df_titanic.pclass==1) & (df_titanic.survived==0)].value_counts())

this code produce true values but I need that in 3 pie chart

df_titanic.groupby(['pclass' ,'survived']).size().plot(kind='pie', autopct='%.2f')

class: 1,2,3 survived: 0,1

CodePudding user response：

1. The correct way to get subplots using pandas, is to reshape the dataframe.

   Unformatted Figure

   axes = ct.plot(kind='pie', autopct='%.1f%%', subplots=True, figsize=(12, 5), labels=["not survived", "survived"])
   

   

   CodePudding user response：

   Code:

   labels = ["not survived", "survived"]
   fig, axs = plt.subplots(1,3)
   axs[0].pie(df_titanic[df_titanic["Pclass"] == 1].groupby(["Survived"]).size(), labels=labels, autopct='%1.1f%%')
   axs[1].pie(df_titanic[df_titanic["Pclass"] == 2].groupby(["Survived"]).size(), labels=labels, autopct='%1.1f%%')
   axs[2].pie(df_titanic[df_titanic["Pclass"] == 3].groupby(["Survived"]).size(), labels=labels, autopct='%1.1f%%')
   plt.show()
   

   Results: