Sort the Pandas DataFrame by two or more columns
In this article, our basic task is to sort the data frame based on two or more columns. For this, Dataframe.sort_values() method is used. This method sorts the data frame in Ascending or Descending order according to the columns passed inside the function.
First, Let’s Create a Dataframe:
Python3
#import python libraryimport pandas as pd # dictionarydata_frame = { 'name': ['Akash Kumar', 'Diksha Tewari', 'Bhawna Gourh', 'Ayush Sharma'], 'age': [20, 21, 22, 23], 'favorite_color': ['black', 'Yellow', 'Pink', "Orange"], 'grade': [88, 92, 95, 70]} # create data frame with indexingdf = pd.DataFrame(data_frame, index = [1, 2, 3, 4]) # printing the dataframedf |
Output:
Example 1: Sort Dataframe based on ‘age'(in descending order) and ‘grade’ (in ascending order) column.
Python3
# sort the dataframe# based on age and gradedf.sort_values(['age', 'grade'], ascending = [False, True]) |
Output:
Example 2: Sort Dataframe based on ‘name’ and ‘favorite_color’ column in ascending order.
Python3
# sort the dataframe based # on name and favorite_colrdf.sort_values(['name', 'favorite_color'], ascending=[True, True]) |
Output:
Example 3: In-place sorting of Dataframe based on ‘grade’ and ‘favorite_color’ column. In case of in-place sorting, Dataframe.sort_values() method returns nothing it performs changes in the actual dataframe.
Python3
df.sort_values(["grade", "favorite_color"], axis = 0, ascending = True, inplace = True, na_position ='first') # printing the dataframedf |
Output:
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