Pandas DataFrame quantile() Method | Find Quantile Values Last Updated : 01 Feb, 2024 Summarize Comments Improve Suggest changes Share Like Article Like Report Python is a great language for data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages, making importing and analyzing data much easier. Pandas quantile() function returns values at the given quantile over the requested axis. Note: In each of any set of values of a variate which divides a frequency distribution into equal groups, each containing the same fraction of the total population. Example: Python3 # importing pandas as pd import pandas as pd # Creating the dataframe df = pd.DataFrame({"A":[1, 5, 3, 4, 2], "B":[3, 2, 4, 3, 4], "C":[2, 2, 7, 3, 4], "D":[4, 3, 6, 12, 7]}) # Print the dataframe df Output: Syntax Syntax: DataFrame.quantile(q=0.5, axis=0, numeric_only=True, interpolation='linear') Parameters : q : float or array-like, default 0.5 (50% quantile). 0 <= q <= 1, the quantile(s) to compute axis : [{0, 1, ‘index’, ‘columns’} (default 0)] 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise numeric_only : If False, the quantile of datetime and timedelta data will be computed as well interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} Returns : quantiles : Series or DataFrame -> If q is an array, a DataFrame will be returned where the index is q, the columns are the columns of self, and the values are the quantiles. -> If q is a float, a Series will be returned where the index is the columns of self and the values are the quantiles. ExamplesLet's see some examples of how to find values of a given quantile using the quantile() function of the Pandas library. Below are the Python codes that illustrates the working of the quantile method on a DataFrame with output. Example 1 Let's use the dataframe.quantile() function to find the quantile of '.2' for each column in the DataFrame. Python3 # find the product over the index axis df.quantile(.2, axis = 0) Output : Example 2 Use the quantile() function to find the (.1, .25, .5, .75) quantiles along the index axis. Python3 # importing pandas as pd import pandas as pd # Creating the dataframe df = pd.DataFrame({"A":[1, 5, 3, 4, 2], "B":[3, 2, 4, 3, 4], "C":[2, 2, 7, 3, 4], "D":[4, 3, 6, 12, 7]}) # using quantile() function to # find the quantiles over the index axis df.quantile([.1, .25, .5, .75], axis = 0) Output : Comment More infoAdvertise with us Next Article Get First and Second Largest Values in Pandas DataFrame S Shubham__Ranjan Follow Improve Article Tags : Technical Scripter Python Python-pandas Python pandas-dataFrame Pandas-DataFrame-Methods +1 More Practice Tags : python Similar Reads Methods to Round Values in Pandas DataFrame There are various ways to Round Values in Pandas DataFrame so let's see each one by one: Let's create a Dataframe with 'Data Entry' Column only: Code: Python3 # import Dataframe class # from pandas library from pandas import DataFrame # import numpy library import numpy as np # dictionary Myvalue = 3 min read Finding the Quantile and Decile Ranks of a Pandas DataFrame column A Quantile is where a sample is divided into equal-sized, adjacent, subgroups. The median is a quantile; the median is placed in a probability distribution so that exactly half of the data is lower than the median and half of the data is above the median. The median cuts a distribution into two equ 4 min read Get First and Second Largest Values in Pandas DataFrame When analyzing data in Python using the pandas library, you may encounter situations where you need to find the highest and second-highest values in a DataFrame's columns. This task can be crucial in various contexts, such as ranking, filtering top performers, or performing threshold-based analysis. 4 min read Pandas DataFrame describe() Method The describe() method in Pandas generates descriptive statistics of DataFrame columns which provides key metrics like mean, standard deviation, percentiles and more. It works with numeric data by default but can also handle categorical data which offers insights like the most frequent value and the 4 min read Percentile rank of a column in a Pandas DataFrame Let us see how to find the percentile rank of a column in a Pandas DataFrame. We will use the rank() function with the argument pct = True to find the percentile rank. Example 1 : Python3 # import the module import pandas as pd # create a DataFrame data = {'Name': ['Mukul', 'Rohan', 'Mayank', 'Shubh 1 min read Sorting a Boxplot by the Median Values in Pandas Boxplots are a powerful tool for visualizing the distribution of data, as they provide insights into the spread, quartiles, and outliers within datasets. However, when dealing with multiple groups or categories, sorting the boxplots by a specific measureâsuch as the medianâcan improve clarity and he 5 min read Like