How to Drop rows in DataFrame by conditions on column values in Python ?
Pandas drop rows by condition: In this article we will discuss how we can delete rows in a dataframe by certain conditions on column values.
DataFrame provides a member function drop() which is used to drop specified labels from rows or columns in dataframe.
DataFrame.drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors=’raise’)
Let’s try with an example:
#Program :
import pandas as pd
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
('anjali',28,'agra','dog','lily'),
('tia',42,'jaipur','elephant','lotus'),
('kapil',51,'patna','cow','tulip'),
('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
print(df)
Output: Name Age Place Animal Flower a riya 37 delhi cat rose b anjali 28 agra dog lily c tia 42 jaipur elephant lotus d kapil 51 patna cow tulip e raj 30 banglore lion orchid
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Delete rows based on condition on a column
Drop rows pandas condition: Let’s try with an example by deleting a row:
deleteRow = df[df['Place'] == 'patna'].index df.drop(deleteRow, inplace=True) print(df)
Output: Name Age Place Animal Flower a riya 37 delhi cat rose b anjali 28 agra dog lily c tia 42 jaipur elephant lotus e raj 30 banglore lion orchid
Here, we give the condition i.e
df[‘Place’] == ‘patna’
Internally if we will see it is giving series object with True and False.
a False b False c False d True e False
Name: Place, dtype: bool
Delete rows based on multiple conditions on a column :
Dataframe drop rows by condition: Let’s try with multiple conditions
deleteRow = df[(df['Age'] >= 30) & (df['Age'] <= 40)].index df.drop(deleteRow, inplace=True) print(df)
Output: Name Age Place Animal Flower b anjali 28 agra dog lily c tia 42 jaipur elephant lotus
Here, we join two conditions i.e df[‘Age’]>=30 and df[‘Age’]<=40 by putting ’&’ between two conditions.
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