replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)replacing values in pandas dataframe
df['coloum'] = df['coloum'].replace(['value_1','valu_2'],'new_value')python replace pandas df elements if they aren't in a list
# Basic syntax:
df.loc[~df['col_name'].isin(list_of_allowed_vals), "col_name"] = "None"
# Example usage:
# Build example dataframe:
dataframe = pd.DataFrame(['ok','keep','wtf','ok'], columns=['col_name'])
print(dataframe)
col_name
0 ok
1 keep
2 wtf
3 ok
list_of_allowed_vals = ['ok', 'keep'] # Define list of elements to keep
# Replace values that aren't the list of allowed values with "None":
dataframe.loc[~dataframe['col_name'].isin(list_of_allowed_vals), "col_name"] = "None"
print(dataframe)
col_name
0 ok
1 keep
2 None
3 ok
# If you want to do this on all columns of the dataframe, run:
dataframe[~dataframe.isin(list_of_allowed_vals)] = "None"Copyright © 2021 Codeinu
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