In this article, we will discuss how to select a single column in a data frame. Now let us try to implement this using Python.
First, let’s create a dataframe
Python3
# importing pandas as library import pandas as pd # creating data frame: df = pd.DataFrame({ 'name' : [ 'Akash' , 'Ayush' , 'Ashish' , 'Diksha' , 'Shivani' ], 'Age' : [ 21 , 25 , 23 , 22 , 18 ], 'Interest' : [ 'Coding' , 'Playing' , 'Drawing' , 'Akku' , 'Swimming' ]}) print ( "The original data frame" ) df |
Output:
Method 1: Using Dot(dataframe.columnname) returns the complete selected column
Python3
# using dot method print ( "Single column value using dataframe.dot" ) print (df.Interest) |
Output:
Method 2: Using dataframe[columnname] method:
There are some problems that may occur with using dataframe.dot are as follows:
- Through dot method, we cannot Select column names with spaces.
- Ambiguity may occur when we Select column names that have the same name as methods for example max method of dataframe.
- We cannot Select multiple columns using dot method.
- We cannot Set new columns using dot method.
Because of the above reason dataframe[columnname] method is used widely.
Python3
# using dataframe[columnname]method print ( "Single column value using dataframe[]" ) print (df[ 'Interest' ]) |
Output:
Another Example now if we want to select the column Age.
Python3
# using dataframe[columnname]method print ( "Single column value using dataframe[]" ) print (df[ 'Age' ]) |
Output: