Articles

drop column pandas dataframe | drop multiple columns in pandas examples

drop column pandas dataframe | drop multiple columns in pandas examples


In this pandas tutorial, we will discuss about:

  • drop column pandas dataframe,
  • drop column in pandas example,
  • drop multiple columns in pandas,
  • drop multiple columns pandas using index

DataFrame is an two dimensional data structure that will store data in two dimensional format. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns.

 

We can able to create this DataFrame using DataFrame() method. But this is available in pandas module, so we have to import pandas module.

Syntax:

pandas.DataFrame(data)

Where, data is the input dataframe, The data can be a dictionary that stores list of values with specified key.

 

Example: Create DataFrame

In this example, we will create dataframe with 4 rows and 4 columns with college data and assign indices through index parameter.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   },index=['one','two','three','four'])

#display the dataframe
print(data)

Output: Dataframe is created below

      college_id       college_name college_address  Total Staff
one        c-001  vignan university          guntur         1200
two        c-021               vvit          guntur         3422
three      c-002           RVR - JC          guntur         5644
four       c-004  Andhra University          guntur          670

Now lets drop column pandas dataframe.


Drop column pandas dataframe

Lets see few ways we can drop column in pandas.

 

Method 1drop column in pandas using drop() with column label

Here, we will use drop() function to remove/drop the columns from the given dataframe. We have to specify the column name/label to drop particular column.

 

So based on the label, it will drop particular column.

Syntax:

dataframe.drop('column_label',axis=1)

where,

  1. dataframe is the input pandas DataFrame.
  2. column_label specifies the column name.
  3. axis=1 specifies the column.

Example: drop column in pandas demo

In this drop column in pandas example, we will display the dataframe by dropping college_id column.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   },index=['one','two','three','four'])

#display the dataframe by dropping college_id column
print(data.drop('college_id',axis=1))

Outputdrop column in pandas result where college_id column is dropped.

            college_name college_address  Total Staff
one    vignan university          guntur         1200
two                 vvit          guntur         3422
three           RVR - JC          guntur         5644
four   Andhra University          guntur          670

In the above code, we are removing/ dropping college_id column and displaying the entire dataframe.

 

Drop multiple columns in pandas

We can also drop multiple columns at a time. Just pass a list of column names to be removed inside drop() function.

 

Exampledrop column in pandas example 2

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   },index=['one','two','three','four'])

#display the dataframe by dropping college_id, college_address and college_name  columns
print(data.drop(['college_id','college_address','college_name'],axis=1))

Outputdrop multiple columns in pandas result is given below

       Total Staff
one           1200
two           3422
three         5644
four           670

In the above code, we are removing/ dropping college_id,college_address,college_name columns and displaying the entire dataframe.

 

This drop column in pandas example shows how we can drop multiple columns from dataframe at same time.


Method 2drop column in pandas using drop() with column position

Here, we will use drop() function to remove/drop the column from the given dataframe. We have to specify the column position to drop particular column.

 

column position starts with 0.

So based on the position, it will drop particular column. We can use dataframe.columns method to represent the column position.

Syntax:

dataframe.drop(dataframe.columns[column_position],axis=1)

where,

  1. dataframe is the input pandas DataFrame.
  2. column_position parameter specifies the column position in columns method.
  3. axis =1 specifies the column.

Example: drop column in pandas by column position

In this example, we will display the dataframe by dropping college_id column.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   },index=['one','two','three','four'])

#display the dataframe by dropping college_id column
print(data.drop(data.columns[0],axis=1))

Outputdrop column in pandas result is given below

            college_name college_address  Total Staff
one    vignan university          guntur         1200
two                 vvit          guntur         3422
three           RVR - JC          guntur         5644
four   Andhra University          guntur          670

From  the above code, the output will be college_name, college_address and Total Staff columns data

because, we dropped the college_id column.

 

drop multiple columns in pandas using column position

We can also drop multiple columns in pandas at a time. Just pass a list of column positions to be removed inside drop() function.

 

Exampledrop multiple columns in pandas by specifying the respective column position is given below

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   },index=['one','two','three','four'])

#display the dataframe by dropping college_id, college_address and college_name  columns
print(data.drop([data.columns[0],data.columns[1],data.columns[2]],axis=1))

Output: drop multiple columns pandas using index result is given below

       Total Staff
one           1200
two           3422
three         5644
four           670

From  the above code, the output will be  Total Staff column data because, we dropped the  college_id,college_name and college_address columns.

 

Thus we have seen drop column in pandas and drop multiple columns in pandas examples as well.


Pandas

Would you like to see your article here on tutorialsinhand. Join Write4Us program by tutorialsinhand.com

About the Author
Gottumukkala Sravan Kumar 171FA07058
B.Tech (Hon's) - IT from Vignan's University. Published 800+ Technical Articles on Python, R, Java, C#, LISP, PHP - MySQL and Machine Learning
Page Views :    Published Date : Mar 14,2022  
Please Share this page

Related Articles

Like every other website we use cookies. By using our site you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. Learn more Got it!