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)]select rows from dataframe pandas
from pandas import DataFrame
boxes = {'Color': ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
'Shape': ['Rectangle','Rectangle','Square','Rectangle','Square','Square','Square','Rectangle'],
'Price': [10,15,5,5,10,15,15,5]
}
df = DataFrame(boxes, columns= ['Color','Shape','Price'])
select_color = df.loc[df['Color'] == 'Green']
print (select_color)Copyright © 2021 Codeinu
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