pie chart drawing for a specific column in pandas python

I have a dataframe df, which has many columns. In df["house_electricity"], there are values like 1,0 or blank/NA. I want to plot the column in terms of a pie chart, where percentage of only 1 and 0 will be shown. Similarly I want to plot another pie chart where percentage of 1,0 and blank/N.A all will be there.

| customer_id | house_electricity | house_refrigerator |
| -------- | -------- |
| cid01 | 0 | 0 |
| cid02 | 1 |na |
| cid03 | | 1 |
| cid04 |1 | |
| cid05 |na | 0 |

#I wrote the following but it didnt give my my expected result
import pandas as pd
import matplotlib.pyplot as plt

df=pd.read_csv("my_file.csv")

df_col=df.columns



df["house_electricity"].plot(kind="pie")

#I wrote the following but it didnt give my my expected result
import pandas as pd
import matplotlib.pyplot as plt

df=pd.read_csv("my_file.csv")

df_col=df.columns



df["house_electricity"].plot(kind="pie")

For a dataframe

df = pd.DataFrame({'a':[1,0,np.nan,1,1,1,'',0,0,np.nan]})
df

a
0	1
1	0
2	NaN
3	1
4	1
5	1
6	
7	0
8	0
9	NaN

The code below will give

df["a"].value_counts(dropna=False).plot(kind="pie")

If you want combine na and empty value, try replacing empty values with np.nan, then try to plot

df["a"].replace("", np.nan).value_counts(dropna=False).plot(kind="pie")

For solution you need to try with this code to generate 3 blocks.

import pandas as pd
import matplotlib.pyplot as plt

data = {'customer_id': ['cid01', 'cid02', 'cid03', 'cid04', 'cid05'],
        'house_electricity': [0, 1, None, 1, None],
        'house_refrigerator': [0, None, 1, None, 0]}

df = pd.DataFrame(data)

counts = df['house_electricity'].value_counts(dropna=False)
counts.plot.pie(autopct='%1.1f%%', labels=['0', '1', 'NaN'], shadow=True)

plt.title('Percentage distribution of house_electricity column')

plt.axis('equal')
plt.show()

Result: