Finding Descriptive Statistics Of A Pandas Series


  • The function Series.describe() computes the Summary Statistics/Descriptive Statistics for the data present in a pandas Series.
  • The summary statistics returned by the Series.describe()  function include,
    • Count – The Number of elements present in the series
    • Mean i.e., the average value
    • Standard Deviation – How for a value in the distribution is away from the mean
    • Min – The minimum value of the distribution
    • Quartiles – The three quartiles that divide the distribution into four equal parts i.e., 25th percentile, 50th percentile and 75th percentile. Given these percentile values the inter quartile distance can be calculated as well.
    • Max – The maximum value of the distribution
    • Using the Max and Min values the Range of the distribution can be calculated.


  • The Python example code loads the rivers.csv file from the R Datasets package (Data Courtesy: The R Datasets Package)into a pandas DataFrame.

Rivers.csv file from the R Datasets Package

  • From the DataFrame only the column “dat” that holds the lengths of rivers in USA is selected into a pandas Series.
  • Calling describe() on the Series instance returns the summary statistics as printed in the output.

# Example Python program to compute Descriptive Statistics

# for a pandas series (Data Courtesy: The R Datasets Package)

import pandas as pds


# Load the data from the rivers.csv

dataFile = "./rivers.csv";

df = pds.read_csv(dataFile);


# Get only the river length column of the DataFrame as a series

riverLength = df["dat"];


# Compute Descriptive statistics for river lengths in the USA

summaryStats = riverLength.describe();


print("Summary statistics for lengths of rivers in USA");




Summary statistics for lengths of rivers in USA

count     141.000000

mean      591.184397

std       493.870842

min       135.000000

25%       310.000000

50%       425.000000

75%       680.000000

max      3710.000000

Name: dat, dtype: float64


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