Select rows from a DataFrame based on column values?
#To select rows whose column value equals a scalar, some_value, use ==:
df.loc[df['A'] == 'foo']
#To select rows whose column value is in an iterable, some_values, use isin:
df.loc[df['B'].isin(['one','three'])]
#Combine multiple conditions with &:
df.loc[(df['column_name'] >= A) & (df['column_name'] <= B)]find rows in dataframe from another dataframe python
common = df1.merge(df2,on=['col1','col2'])
print(common)
df1[(~df1.col1.isin(common.col1))&(~df1.col2.isin(common.col2))]Copyright © 2021 Codeinu
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