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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