Python Pandas Tutorial 3: Different Ways Of Creating DataFrame




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This tutorial covers 5 different ways of creating pandas dataframe. Pandas is a popular python library especially used in data science and data analytics.

Topics that are covered in this Python Pandas Video:
0:00 Introduction
0:41 How to create dataframe?
1:11 Create dataframe using read_csv() method
1:58 Create dataframe using read_excel() method
2:55 Create dataframe using python dictionary DataFrame() method
4:00 Create dataframe using tuples list DataFrame() method
5:18 Create dataframe using the list of dictionary DataFrame() method
6:34 Other ways to create dataframe

code/data link: https://github.com/codebasics/py/tree/master/pandas/3_different_ways_of_creating_dataframe

Next Video:
Python Pandas Tutorial 4: Read Write Excel CSV File
https://www.youtube.com/watch?v=-0NwrcZOKhQ&list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy&index=4

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Comment List

  • codebasics
    November 29, 2020

    Hello, what does the r before C: ?
    df = pd.csv_read(r 'C:datasetsexample.csv')
    With some letters of the lowercase alphabet from error if there is not.
    thx
    ric

  • codebasics
    November 29, 2020

    Awesome information ❤️

  • codebasics
    November 29, 2020

    Sir i want the answer for
    Write the syntax of dataframe method?

  • codebasics
    November 29, 2020

    thank you!!

  • codebasics
    November 29, 2020

    Simple ! And easy

  • codebasics
    November 29, 2020

    Thanks man such a great vedio

  • codebasics
    November 29, 2020

    Sir I have one error, dataframe object has not attribute dataframe

  • codebasics
    November 29, 2020

    i am not able to open the csv file it is giving me error
    UnicodeDecodeError: 'utf-8' codec can't decode byte 0xae in position 16: invalid start byte
    Give me solution

  • codebasics
    November 29, 2020

    Thank you for awesome tutorials! I am getting back to hands on after long and am loving it!

    I had a quick question, what would be the easiest way to download/print Jupyter notebooks/code from Github repository. Any ideas would be appreciated.

    Ajay

  • codebasics
    November 29, 2020

    Boss, I am using the same Jupyter notebook, but I could'nt see border lines in df across rows and columns, could you please help in this.

  • codebasics
    November 29, 2020

    Thanks sir
    There tutorials are really helpful

  • codebasics
    November 29, 2020

    👍

  • codebasics
    November 29, 2020

    Simple and efficient … Thank you

  • codebasics
    November 29, 2020

    do we need "pip install xlrd" for read_csv?

  • codebasics
    November 29, 2020

    Thank you for teaching me Basics of Pandas..

  • codebasics
    November 29, 2020

    Step by step roadmap to learn data science in 6 months: https://www.youtube.com/watch?v=H4YcqULY1-Q
    Machine learning tutorials with exercises:

    https://www.youtube.com/watch?v=gmvvaobm7eQ&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw

  • codebasics
    November 29, 2020

    How to add return value from function to dataframe column?

  • codebasics
    November 29, 2020

    Thank you for making the concept so easy and simple .I am worried about the people why gave "thumbs down" wishing if they know better let us know with the proof of video tutorials-——-you thumbs downer—-

  • codebasics
    November 29, 2020

    install xlrd if unable to read excel file

  • codebasics
    November 29, 2020

    Nice and well-explained videos.

  • codebasics
    November 29, 2020

    This should save you some time! Here is the text he copied and pasted for examples 3 through 5

    # way 3 (python dictionary)

    weather_data = {

    'day': ['1/1/2017', '1/2/2017', '1/3/2017'],

    'temperature': [32, 35, 28],

    'windspeed': [6,7,2],

    'event': ['Rain', 'Sunny', 'Snow']

    }

    # way 4 (python tuple list)

    weather_data = [

    ('1/1/2017', 32, 6, 'Rain'),

    ('1/2/2017', 35, 7, 'Sunny'),

    ('1/3/2017', 28, 2, 'Snow')

    ]

    # way 5 (python dictionary list)

    weather_data = [

    {'day': '1/1/2017', 'temperature': 32, 'windspeed': 6, 'event': 'Rain'},

    {'day': '1/2/2017', 'temperature': 35, 'windspeed': 7, 'event': 'Sunny'},

    {'day': '1/3/2017', 'temperature': 28, 'windspeed': 2, 'event': 'Snow'}

    ]

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