Contact Us

Contact Form

Comments

Post a Comment

Popular posts from this blog

Descriptive statistics - mode(), mean() and median()

C. mode() - returns the value that appears most from a set of values. Example:- 1. import pandas as pd import pandas as pd df2 = pd.DataFrame({2016:{'q1':500,'q2':500,'q3':47000,'q4':49000},2017:{'q1':'A','q2':'A','q3':'A','q4':'D'},2018:{'q1':54500,'q2':51000}}) df2.mode() Output:- 2016 2017 2018 0 500.0 A 51000.0 1 NaN NaN 54500.0 Explanation:- Since by default axis=0 so mode is calculated among rows(indexes) i.e for each column. 2. df2.mode(axis=1) 0 1 2 q1 500 A 54500.0 q2 500 A 51000.0 q3 47000 A NaN q4 49000 D NaN Explanation:- Since axis=1 so the mode is calculated among columns i.e for each row. 3.  df2.mode(numeric_only=True) Output:- 2016 2018 0 500.0 51000.0 1 NaN 54500.0 Explanation: With numeric_only=True only numeric values are included for mode calculation and String/Text values are not considered. By...
Read more

Python class 11 'IP' Basics

Python is a Programming language used to create software, websites and for scientific computing. Programming language is a language that can be used to write programs to give instructions to computer to perform a specific task. Other popular programming language are C, C++, Java, VB, C# and JavaScript. Popularity of python can be attributed to its huge library(collection of modules, functions) that can be used by the programmer to build any program in less time and effort than any other programming language. Data Science and Machine learning are the two buzzwords that's been around quite some time and to implement techniques of data science and machine learning python is the tool of choice for most programmers. Advantages of Python Language are:- Easy to use - Programmers find it very easy to use it because the rules(syntax) for writing instructions are very much similar to other high level language(C, C++, Java). Expressive Language - Requires fewer lines of code to...
Read more

Descriptive Statistics - min(), max()

A. min() - Find out the minimum and maximum out of a given set of data. Example:- import pandas as pd df = pd.DataFrame({2016:{'q1':34500,'q2':56000,'q3':47000,'q4':49000},2017:\{'q1':44900,'q2':46100,'q3':57000,'q4':59000},2018:{'q1':54500,'q2':51000}}) print(df) Output:- 2016 2017 2018 q1 34500 44900 54500.0 q2 56000 46100 51000.0 q3 47000 57000 NaN q4 49000 59000 NaN 1. print(df.min()) Output:- 2016 34500.0 2017 44900.0 2018 51000.0 Explanation: min() finds the minimum among the indexes for each column and axis 0 by default. 2. print(df.min(axis=1)) Output:- q1 34500.0 q2 46100.0 q3 47000.0 q4 49000.0 Explanation: min(axis=1) finds the minimum among the columns for each indexes. import pandas as pd df2 = pd.DataFrame({2016:{'q1':34500,'q2':56000,'q3':47000,'q4':49000},2017:{'q1':'A','q2':'B...
Read more