PYTHON

only keep rows of a dataframe based on a column value

df.loc[df['column_name'] == some_value]

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)]

only keep rows of a dataframe based on a column value

df.loc[(df['column_name'] >= A) & (df['column_name'] <= B)]

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)]