We can easily reshape the data by categorizing a specific column. Here, we will categorize the “Result”column i.e. Pass and Fail values in numbers form.
Import the required library −
import pandas as pd
Create a DataFrame with 2 columns −
dataFrame = pd.DataFrame( { "Student": ['Jack', 'Robin', 'Ted', 'Scarlett', 'Kat'],"Result": ['Pass', 'Fail', 'Fail', 'Pass', 'Pass'] } )
Reshape the data using the map() function and just set ‘Pass’ to 1 and ‘Fail’ to 0 −
dataFrame['Result'] = dataFrame['Result'].map({'Pass': 1,'Fail': 0, })
Example
Following is the code −
import pandas as pd # Create DataFrame dataFrame = pd.DataFrame( { "Student": ['Jack', 'Robin', 'Ted', 'Scarlett', 'Kat'],"Result": ['Pass', 'Fail', 'Fail', 'Pass', 'Pass'] } ) print"DataFrame ...\n",dataFrame # reshaping into numbers dataFrame['Result'] = dataFrame['Result'].map({'Pass': 1,'Fail': 0, }) print"\nReshaped DataFrame ...\n",dataFrame
Output
This will produce the following output
DataFrame ... Result Student 0 Pass Jack 1 Fail Robin 2 Fail Ted 3 Pass Scarlett 4 Pass Kat Reshaped DataFrame ... Result Student 0 1 Jack 1 0 Robin 2 0 Ted 3 1 Scarlett 4 1 Kat