In this article, we will discuss how to get the first column of the pandas dataframe in Python programming language.
Method 1: Using iloc[] function
This function is used to get the first column using slice operator. for the rows we extract all of them, for columns specify the index for first column.
Syntax :
dataframe.iloc[:, 0]
where. dataframe is the input dataframe
The slice operation will be like:
[row_start:row_end , column_start, column_end]
where,
- row_start refers start row with 0 position as index
- row_end refers last row with n th position as index
- column_start refers start column with 0 position as index
- column_end refers last column with n th position as index
The following alternative can also be employed.
Syntax :
dataframe.iloc[:, :1]
where. dataframe is the input dataframe. Both of these will return the dataframe datatype.
Example: Python program to get the first column by using above approaches
Python3
# import pandas module import pandas as pd # create dataframe with 3 columns data = pd.DataFrame({ "id" : [ 7058 , 7059 , 7072 , 7054 ], "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'python' , 'html/php' , 'php/js' ] } ) # display dataframe print (data) print ( "--------------" ) # get first column by returning series print (data.iloc[:, 0 ]) print ( "--------------" ) # get first column by returning dataframe print (data.iloc[:, : 1 ]) |
Output:
Method 2 : Using columns[]
This method will return the column based on index. So, we have to give 0 to get the first column
Syntax:
dataframe[dataframe.columns[0]]
where
- dataframe is the input dataframe
- columns[0] represent first column
Example: Python program to get the first column using columns[]
Python3
# import pandas module import pandas as pd # create dataframe with 3 columns data = pd.DataFrame({ "id" : [ 7058 , 7059 , 7072 , 7054 ], "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'python' , 'html/php' , 'php/js' ] } ) # display dataframe print (data) print ( "--------------" ) # get first column by returning dataframe # using columns[] method print (data[data.columns[ 0 ]]) |
Output:
Method 3: Using column name
We can use the first column name to get the first column.
Syntax:
dataframe.first_column
Example: Python code to get the first column using column name
Python3
# import pandas module import pandas as pd # create dataframe with 3 columns data = pd.DataFrame({ "id" : [ 7058 , 7059 , 7072 , 7054 ], "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'python' , 'html/php' , 'php/js' ] } ) # display dataframe print (data) print ( "--------------" ) # get first column by returning dataframe # using column_name print (data. id ) |
Output:
We can also use the head() function within this to display the number of rows in the first column.
Example: Python code to get the first column using the column name
Python3
# import pandas module import pandas as pd # create dataframe with 3 columns data = pd.DataFrame({ "id" : [ 7058 , 7059 , 7072 , 7054 ], "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'python' , 'html/php' , 'php/js' ] } ) # display dataframe print (data) print ( "--------------" ) # get first column by returning dataframe # using column_name # display 1 row print (data. id .head( 1 )) print ( "--------------" ) # get first column by returning dataframe # using column_name # display 2 rows print (data. id .head( 2 )) print ( "--------------" ) # get first column by returning dataframe # using column_name # display 4 rows print (data. id .head( 4 )) |
Output:
Method 4: Using head() function
This function by default returns the top rows of the dataframe. To return the column we have to Transpose (Interchange rows to columns) the dataframe by using T function and get 1st column.
Syntax:
dataframe.T.head(1).T
Example: Python code to get the first column using column name
Python3
# import pandas module import pandas as pd # create dataframe with 3 columns data = pd.DataFrame({ "id" : [ 7058 , 7059 , 7072 , 7054 ], "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'python' , 'html/php' , 'php/js' ] } ) # display dataframe print (data) print ( "--------------" ) # using head print (data.T.head( 1 ).T) |
Output: