Replacing NaN with None in Pandas

Example 1: The data frame, for which ‘Nan’ is to be replaced with ‘None’, is as follows:

The provided code uses the Pandas library to replace ‘NaN’ values in a DataFrame df with ‘None’. It does so by using the replace() method with a dictionary mapping where keys (in this case, ‘np.nan’) are replaced by their corresponding values (in this case, ‘None’). The resulting DataFrame ‘replaced_df’ contains ‘None’ in place of ‘NaN’ values.

Python3




import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan,3], 'B': [np.nan, 5, 6], 'C': [7, 8, np.nan]})
replaced_df = df.replace({np.nan: None})
print(replaced_df)


Output:

Example 2: The data frame, for which ‘Nan’ is to be replaced with ‘None’, is as follows:

The provided code uses the Pandas library to replace ‘NaN’ values in a DataFrame df with ‘None’. It does so by using the replace() method with a dictionary mapping where keys (in this case, ‘np.nan’) are replaced by their corresponding values (in this case, ‘None’). The resulting DataFrame ‘replaced_df’ contains ‘None’ in place of ‘NaN’ values.

Python3




import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [np.nan,6 ,3], 'B': [9, 5, np.nan], 'C': [np.nan, 8,5 ]})
print(df)
replaced_df = df.replace({np.nan: None})
print(replaced_df)


Output

Replacing Pandas or Numpy Nan with a None to use with MysqlDB

The widely used relational database management system is known as MysqlDB. The MysqlDB doesn’t understand and accept the value of ‘Nan’, thus there is a need to convert the ‘Nan’ value coming from Pandas or Numpy to ‘None’. In this article, we will see how we can replace Pandas or Numpy ‘Nan’ with a ‘None’.

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