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Data Analysis with Python and Pandas

Video Description

This course is aimed at teaching the fundamentals of data analysis with Python. The go-to module in Python for data analysis and manipulation is Pandas, which is built on top of other popular modules, such as NumPy. Pandas also works with many other data science modules, such as the machine learning framework, Scikit-Learn. The Pandas module allows you to import and export data in a variety of forms like csv, json, hdf, sql, and more. From here, Pandas helps you quickly organize this data into a columns and rows format, which is the same no matter what the input data format is. From here, you can manipulate entire columns, create new ones, apply functions to data points, perform statistical analysis, and more.

Table of Contents

  1. 1.Introduction
    1. Course Introduction 00:04:11
    2. Getting pandas and fundamentals 00:09:07
    3. Section Conclusion 00:02:42
  2. 2.Introduction to Pandas
    1. Section Introduction 00:00:48
    2. Creating & Navigating a Dataframe 00:08:35
    3. Slices, head and tail 00:07:59
    4. Indexing 00:07:27
    5. Visualizing The Data 00:09:19
    6. Converting To Python List Or Pandas Series 00:04:16
    7. Section Conclusion 00:01:39
  3. 3.IO Tools
    1. Section Introduction 00:02:13
    2. Read Csv And To Csv 00:09:27
    3. io operations 00:05:24
    4. Read_hdf and to_hdf 00:08:25
    5. Read Json And To Json 00:09:55
    6. Read Pickle And To Pickle 00:11:39
    7. Section Conclusion 00:03:52
  4. 4.Pandas Operations
    1. Section Introduction 00:02:04
    2. Column Manipulation 00:07:27
    3. Column & Dataframe logical categorization 00:07:13
    4. Statistical Functions Against Data 00:07:34
    5. Moving & rolling statistics 00:10:00
    6. Rolling apply 00:08:55
    7. Section Conclusion 00:03:18
  5. 5.Handling for Missing Data / Outliers
    1. Section Introduction 00:03:13
    2. Drop na 00:06:48
    3. Filling Forward And Backward Na 00:11:09
    4. Detecting outliers 00:12:36
    5. Section Conclusion 00:05:18
  6. 6.Combining Dataframes
    1. Section Introduction 00:03:54
    2. Concatenation 00:09:16
    3. Appending data frames 00:07:07
    4. Merging dataframes 00:09:41
    5. Joining dataframes 00:09:41
    6. Section Conclusion 00:04:29
  7. 7.Advanced Operations
    1. Section Introduction 00:02:48
    2. Basic Sorting 00:08:56
    3. Sorting by multiple rules 00:08:32
    4. Resampling basics time & how 00:10:03
    5. Resampling to ohlc 00:07:12
    6. Correlation And Covariance Part1 00:10:04
    7. Correlation and Covariance part 2 00:11:56
    8. Mapping custom functions 00:09:21
    9. Graphing percent change of income groups 00:07:23
    10. Buffering Basics 00:10:12
    11. Buffering Into And Out Of Hdf5 00:10:01
    12. Section Conclusion 00:03:01
  8. 8.Working with Databases
    1. Section Introduction 00:01:00
    2. Writing to reading from database 00:10:22
    3. Resampling data and preparing graph 00:07:55
    4. Finishing Manipulation And Graph 00:09:32
    5. Section and Course Conclusion 00:05:27