Python Pandas Tutorial 2: Dataframe Basics


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This pandas tutorial covers basics on dataframe. DataFrame is a main object of pandas. It is used to represent tabular data (with rows and columns). This tutorial will go over,
1) What is dataframe?
2) Create dataframe from csv file and python dictionary
3) Dealing with rows and columns
4) Operations: mean, max, std, describe
5) Conditional selection
6) set_index function and usefulness of it

32 thoughts on “Python Pandas Tutorial 2: Dataframe Basics

  1. I have a question. I have a text file with some rows and a columns. This column consists of 4 values. but when i print the number of columns, its showing 1. how do i split these four values in the columns?

  2. only half way through and I'm already excited about what I've gained from this! can't wait to try this when I get to the computer. thank you for such clear explanation!!

  3. I uploaded csv file with table data format into jupyter and it was displayed as commas separated values. I've formatted the table into commas values and it displayed data in a desired table format. Does anybody know why tables (.csv) are displayed as commas and commas separated values (.csv) as a proper tables? Thanks for any suggestions.

  4. how to parse row if row contain list ,
    for example:-
    build. delay []. example
    65. 0,200,400. 65.43,54,87

    like this I I want for 0 i want 65.34 and for 200 I want 43 so on how could I do this..

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