missing_values_with_pandas.py

# import packages
import pandas as pd
import numpy as np


# create a sample dataframe
my_df = pd.DataFrame({"A": [1,2,3,np.nan,5,np.nan,7],
                      "B": [4,np.nan,7,np.nan,1,np.nan,2]})


# finding missing values with pandas
my_df.isna()
my_df.isna().sum()


# dropping missing values with pandas
my_df.dropna()
my_df.dropna(how = "any")
my_df.dropna(how = "all")

# for specific columns
my_df.dropna(how = "any", subset = ["A"])

# put the "inplace" parameter to True to apply it permanently to the dataframe
my_df.dropna(how = "any", inplace = True)


# filling missing vaues with pandas
my_df = pd.DataFrame({"A": [1,2,3,np.nan,5,np.nan,7],
                      "B": [4,np.nan,7,np.nan,1,np.nan,2]})

my_df.fillna(value = 100)

mean_value = my_df["A"].mean()
my_df["A"].fillna(value = mean_value)

my_df.fillna(value = my_df.mean(), inplace = True)