Course curriculum

    1. Course Introduction

    2. Pandas

    3. What is Data Wrangling?

    4. Summary

    1. Download Raw Titanic Data Set

    2. Loading the Dataset

    3. Lab: Save Existing Dataframe to CSV

    4. The Shape of the Data

    5. Subsetting

    6. Using loc

    7. Using iloc and ix

    8. iloc and ix on Rows and Columns

    9. Lab: Slicing Dataframes

    10. The GroupBy Function

    11. Group By Frequency Count

    12. Lab: Grouping

    1. The Series Object

    2. Series Anatomy

    3. Lab: Series Anatomy

    4. Attributes

    5. Series and ndarray Similarity

    6. The Array

    7. Boolean Subsetting in a Series

    8. Vectorized Operations

    9. Lab: Boolean and Variable Attribute Searches

    10. The Replace Functions

    11. Change Column Header Names

    12. Sorting in a Dataframe

    13. Lab: Descriptive Statistics for Pandas Dataframe

    14. Reading an Excel File

    15. Regular Expressions

    16. Binning

    17. Data Normalization

    18. Lab: Normalizing Data

    1. Concatenation

    2. Row Concatenation

    3. Lab: Concatenation Basics

    4. The Merge Join

    5. The Joins

    6. Lab: Using the Merge Function

    1. Missing Data

    2. Finding the NANS

    3. Lab: Missing Data

    4. Filling Index Values

    5. NAN Value Differences

    6. Changing Cell Values

    7. Interpolation

    8. Handling Duplicates

    9. Mappings

    10. Create a Column With a Function

    11. Replace

    12. Lab: Duplicate Data

    1. Time Series

    2. The Time Stamp Object

    3. Lab: Time Series

    4. The Time Delta Object

    5. The Data Time Index

    6. Force a Data Conversion

    7. The Frequency Parameter

    8. Date Offsets

    9. Anchored Offsets

    10. Period Object

About this course

  • Free
  • 62 lessons
  • 1 hour of video content