By using pandas.DataFrame.drop() method you can remove/delete/drop the list of rows from pandas, all you need to provide is a list of rows indexes or labels as a param to this method. By default drop() method removes the rows and returns a copy of the updated DataFrame instead of replacing the existing referring DataFrame. If you wanted to remove from the DataFrame in place use inplace=True param. By default, the value for inplace property is False meaning not to update the existing DataFrame.
By using the same drop() method, you can also remove columns in pandas DataFrame by using axis=1
1. Create a Sample DataFrame
Let’s create a pandas DataFrame to explain how to remove list of rows with examples, my DataFrame contains the column names Courses, Fee, Duration, and Discount.
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Hadoop","Python","pandas","Oracle","Java"],
'Fee' :[20000,25000,26000,22000,24000,21000,22000],
'Duration':['30day','40days','35days', '40days','60days','50days','55days'],
'Discount':[1000,2300,1500,1200,2500,2100,2000]
}
df = pd.DataFrame(technologies)
print(df)
Yields below output.
Courses Fee Duration Discount
0 Spark 20000 30day 1000
1 PySpark 25000 40days 2300
2 Hadoop 26000 35days 1500
3 Python 22000 40days 1200
4 pandas 24000 60days 2500
5 Oracle 21000 50days 2100
6 Java 22000 55days 2000
2. pandas Drop List of Rows by Index
pandas.DataFrame.drop() function takes a list of indexes/labels that you wanted to delete, this function returns a copy of DataFrame without modifying the reference DataFrame.
# Drop by List of Index position
df1 = df.drop([2,4])
print(df1)
Yields below output.
Table with the dropped rows
Courses Fee Duration Discount
0 Spark 20000 30day 1000
1 PySpark 25000 40days 2300
3 Python 22000 40days 1200
5 Oracle 21000 50days 2100
6 Java 22000 55days 2000
If you wanted to create a new index after removing the list of rows.
# reset index
df = pd.DataFrame(technologies)
df1 = df.drop([2,4]).reset_index()
print(df1)
4. Drop a List of Rows From DataFrame inplace
If you notice by default drop() method returns the copy of the DataFrame after removing rows, but if you wanted to update the existing DataFrame, use inplace=True parameter. when you used inplace=True param, DataFrame returns None instead of DataFrame. For E.x df.drop([3,5], inplace=True) drops the specified list of rows from df object.
df = pd.DataFrame(technologies)
df.drop([2,4],inplace=True)
print(df)
Yields same output as above.
5. Removing Range of Rows From One to Five
You can use python list slicing to delete a list of rows from 1 to 5 for example, df.drop(df.index[:5],inplace= True) function remove one to five rows.
df = pd.DataFrame(technologies)
df.drop(df.index[:5],inplace=True)
print(df)
Yields below output.
Removing Range of Rows from 0 to 5
Courses Fee Duration Discount
5 Oracle 21000 50days 2100
6 Java 22000 55days 2000
6. Drop List of Rows by Index Position in DataFrame
In case if you have index labels on DataFrame, you can also remove the list of rows by position. For example, below removes 3rd and 5th records from DataFrame. Note index starts from zero.
indexes=['r1','r2','r3','r4','r5','r6','r7']
df = pd.DataFrame(technologies,index=indexes)
df.drop(df.index[[2,4]],inplace=True)
print(df)
Yields below output.
Courses Fee Duration Discount
r1 Spark 20000 30day 1000
r2 PySpark 25000 40days 2300
r4 Python 22000 40days 1200
r6 Oracle 21000 50days 2100
r7 Java 22000 55days 2000
You can also try removing the rows by applying pandas filter.
Conclusion
In this article you have learned how to remove a list of DataFrame rows in pandas using the drop() function, also learned how to remove rows by a list of indexes and labels.
Happy Learning !!
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