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Sorting rows in pandas DataFrame
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Ranking Rows of Pandas DataFrame

Last Updated : 14 Jan, 2019
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To rank the rows of Pandas DataFrame we can use the DataFrame.rank() method which returns a rank of every respective index of a series passed. The rank is returned on the basis of position after sorting. Example #1 : Here we will create a DataFrame of movies and rank them based on their ratings. Python3 1== 
# import the required packages  import pandas as pd   # Define the dictionary for converting to dataframe  movies = {'Name': ['The Godfather', 'Bird Box', 'Fight Club'],          'Year': ['1972', '2018', '1999'],          'Rating': ['9.2', '6.8', '8.8']}  df = pd.DataFrame(movies) print(df)
Output: Python3 1== 
# Create a column Rating_Rank which contains # the rank of each movie based on rating df['Rating_Rank'] = df['Rating'].rank(ascending = 1)  # Set the index to newly created column, Rating_Rank df = df.set_index('Rating_Rank') print(df)
Output: Python3 1== 
# Sort the dataFrame based on the index df = df.sort_index() print(df)
Output:   Example #2 Let's take an example of marks scored by 4 students. We will rank the students based on the highest mark they have scored. Python3 1== 
# Create a dictionary with student details student_details = {'Name':['Raj', 'Raj', 'Raj', 'Aravind', 'Aravind', 'Aravind',                              'John', 'John', 'John', 'Arjun', 'Arjun', 'Arjun'],                    'Subject':['Maths', 'Physics', 'Chemistry', 'Maths', 'Physics',                              'Chemistry', 'Maths', 'Physics', 'Chemistry', 'Maths',                                                            'Physics', 'Chemistry'],                    'Marks':[80, 90, 75, 60, 40, 60, 80, 55, 100, 90, 75, 70]                }  # Convert dictionary to a DataFrame df = pd.DataFrame(student_details) print(df)
Output: Python3 1== 
# Create a new column with Marks  # ranked in descending order df['Mark_Rank'] = df['Marks'].rank(ascending = 0)  # Set index to newly created column  df = df.set_index('Mark_Rank') print(df)
Output: Python3 1== 
# Sort the DataFrame based on the index  df = df.sort_index()  print(df)
Output: Explanation: Notice here that we have Raj and Arjun getting 90 marks each and hence they get ranked 2.5 (average of 2nd and 3rd rank i.e the two ranks they share). This can be seen for other marks in the table as well.

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Sorting rows in pandas DataFrame

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    Pandas in Python can convert a Pandas DataFrame to a table in an HTML web page. The pandas.DataFrame.to_html() method is used to render a Pandas DataFrame into an HTML format, allowing for easy display of data in web applications. In this article, we will understand how to use the Styler Object and
    6 min read
    Exporting Pandas DataFrame to JSON File
    Pandas a powerful Python library for data manipulation provides the to_json() function to convert a DataFrame into a JSON file and the read_json() function to read a JSON file into a DataFrame.In this article we will explore how to export a Pandas DataFrame to a JSON file with detailed explanations
    2 min read
    Create and display a one-dimensional array-like object using Pandas in Python
    Series() is a function present in the Pandas library that creates a one-dimensional array and can hold any type of objects or data in it. In this article, let us learn the syntax, create and display one-dimensional array-like object containing an array of data using Pandas library. pandas.Series() S
    2 min read
    Export Pandas dataframe to a CSV file
    When working on a Data Science project one of the key tasks is data management which includes data collection, cleaning and storage. Once our data is cleaned and processed it’s essential to save it in a structured format for further analysis or sharing.A CSV (Comma-Separated Values) file is a widely
    2 min read
    Display the Pandas DataFrame in Heatmap style
    Pandas library in the Python programming language is widely used for its ability to create various kinds of data structures and it also offers many operations to be performed on numeric and time-series data. By displaying a panda dataframe in Heatmap style, the user gets a visualisation of the numer
    6 min read
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