Python: Data Analysis with Pandas Library


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Torrent Hash : 464338B651C35C9D18179D8DF99B7874E74A5611
Torrent Added : 1 Year+ in Other - Other
Torrent Size : 1.65 GB


Python: Data Analysis with Pandas Library
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Torrent File Content (20 files)


Python Data Analysis with Pandas Library [UdemyLibrary.com]
    1. Introduction
          1. Introduction.mp4 -
13.11 MB

          1. Introduction.srt -
2.77 KB

    2. Pandas Data Structures - Series
          1. Pandas Data Structures - Series.mp4 -
144.83 MB

          1. Pandas Data Structures - Series.srt -
25.04 KB

    3. Pandas Data Structures - Dataframes
          1. Dataframes.mp4 -
100.23 MB

          1. Dataframes.srt -
17.01 KB

    4. Playing with Dataframes
          1. Playing with Dataframes.mp4 -
89.61 MB

          1. Playing with Dataframes.srt -
15.8 KB

    5. Selecting columns & rows from a Dataframe
          1. Selecting columns & rows from a Dataframe.mp4 -
140.22 MB

          1. Selecting columns & rows from a Dataframe.srt -
20.02 KB

    6. Subsetting of Dataframes
          1. Subsetting of Dataframes.mp4 -
59.54 MB

          1. Subsetting of Dataframes.srt -
7.64 KB

    7. Indexing
          2. Indexing Part2.mp4 -
594.7 MB

          1. Indexing Part1.mp4 -
48.4 MB

          2. Indexing Part2.srt -
62.89 KB

          1. Indexing Part1.srt -
7.07 KB

    8. Dataframes Merging and Concatenating
          2. Dataframes Merging and Concatenating.mp4 -
495.33 MB

          2. Dataframes Merging and Concatenating.srt -
64.62 KB

          1. CSV Files to be used for dataframes merging and concatenating.html -
155 bytes

     [UdemyLibrary.com] Join for free courses and tutorials.txt -
246 bytes



Description





Python: Data Analysis with Pandas Library

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 9 lectures (4h 5m) | Size: 1.28 GB

Python programming has become one of the most sought after programming languages in the world, with its extensive amount of features and the sheer amount of productivity it provides. Therefore, being able to code Pandas in Python, enables you to tap into the power of the various other features and libraries which will use with Python. Some of these libraries are NumPy, SciPy, MatPlotLib, etc.

covers, more info and reviews in suggested reading order:
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