Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How can data be summarized in Pandas Python?
Lots of information about the data can be obtained by using different functions on it. But if we wish to get all information on the data, the ‘describe’ function can be used.
This function will give information such as ‘count’, ‘mean’, ‘standard deviation’, the 25th percentile, the 50th percentile, and the 75th percentile.
Example
import pandas as pd
my_data = {'Name':pd.Series(['Tom','Jane','Vin','Eve','Will']),
'Age':pd.Series([45, 67, 89, 12, 23]),'value':pd.Series([8.79,23.24,31.98,78.56,90.20])
}
print("The dataframe is :")
my_df = pd.DataFrame(my_data)
print(my_df)
print("The description of data is :")
print(my_df.describe())Output
The dataframe is : Name Age value 0 Tom 45 8.79 1 Jane 67 23.24 2 Vin 89 31.98 3 Eve 12 78.56 4 Will 23 90.20 The description of data is : Age value count 5.000000 5.000000 mean 47.200000 46.554000 std 31.499206 35.747102 min 12.000000 8.790000 25% 23.000000 23.240000 50% 45.000000 31.980000 75% 67.000000 78.560000 max 89.000000 90.200000
Explanation
- The required libraries are imported, and given alias names for ease of use.
- Dictionary of series consisting of key and value is created, wherein a value is actually a series data structure.
- This dictionary is later passed as a parameter to the ‘Dataframe’ function present in the ‘pandas’ library
- The dataframe is printed on the console.
- We are looking at getting all the information about the data.
- The ‘describe’ function is called on the dataframe.
- The description is printed on the console.
Updated on: 10-Dec-2020
58 Views
Advertisements