PYTHON

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 specific rows from dataframe in python

select_color = df.loc[df['Color'] == 'Green']

pandas return specific row

df.iloc[1] # replace index integer with specific row number

how to select rows with specific values in pandas

#To select rows whose column value is in an iterable array, which we'll define as array, you can use isin:
array = ['yellow', 'green']
df.loc[df['favorite_color'].isin(array)]

selecting rows with specific values in pandas

#To select rows whose column value equals a scalar, some_value, use ==:df.loc[df['favorite_color'] == 'yellow']

selecting rows with specific values in pandas

#To select rows whose column value equals a scalar, some_value, use ==:df.loc[df['favorite_color'] == 'yellow']