Pandas for Data Science

What you'll be able to do

• Key data operations
• Data preparation & transformation
• Data grouping & aggregation
• Handling large data
• Pivoting data and combining dataframes
• Data cleaning and transformations
• Data Visualization
• Conditional filtering & sorting
• Speed up the codes

1. 01Introduction to Pandas11 lessons · 30 min

   1. Introduction to Pandas3:19
   2. How to Get Queries Resolved1:00
   3. Download Resources1:00
   4. Need For DataFramePreview3:47
   5. Creating DataFramePreview8:37
   6. Mini ChallengePreview0:48
   7. SeriesPreview7:24
   8. Mini Challenge2:43
   9. Complete ML Mastery1:00
   10. AssignmentFile
   11. Assignment SolutionFile
2. 02Setup Environment2 lessons · 14 min

   1. Python Setup Local Installation9:47
   2. Python Setup Google Colab4:33
3. 03Inspecting Dataframes and Must know operations8 lessons · 21 min

   1. Course Review1:00
   2. Inspecting Dataframes4:51
   3. Renaming Columns4:22
   4. Pandas Summary3:18
   5. Essential Operations4:28
   6. Display Options2:59
   7. AssignmentAssignment
   8. Assignment SolutionAssignment
4. 04Conditional filtering and sorting13 lessons · 42 min

   1. Extracting Specific Part of Data - Part 15:30
   2. Extracting Specific Part of Data - Part 22:06
   3. Mini Challenge1:11
   4. at and iat4:12
   5. Mini Challenge1:32
   6. Filtering Data That Satisfy Conditions5:30
   7. Membership Filtering4:21
   8. Query and Eval4:04
   9. Removing Duplicates3:01
   10. Sorting2:42
   11. Map and Applymap7:54
   12. AssignmentAssignment
   13. Assignment SolutionAssignment
5. 05Data preparation and transformation7 lessons · 21 min

   1. Apply a function rowwise or columnwise7:20
   2. Scaling and Standardization5:05
   3. Make Index as a Dataframe Column2:09
   4. Discretization and Binning5:26
   5. Course Review1:00
   6. AssignmentAssignment
   7. Assignment SolutionAssignment
6. 06Useful tips and tricks8 lessons · 24 min

   1. Random Sampling5:13
   2. Dummy Variables2:03
   3. Categorical Data Part-13:32
   4. Categorical Data Part-23:07
   5. Method Chaining4:08
   6. Efficiently Read Data From Multiple Files5:30
   7. AssignmentAssignment
   8. Assignment SolutionAssignment
7. 07Data grouping and aggregation7 lessons · 17 min

   1. Group by Mechanism6:19
   2. Mini Challenge2:18
   3. Iterating Between Groups3:19
   4. Transform3:54
   5. Course Review1:00
   6. AssignmentAssignment
   7. Assignment SolutionAssignment
8. 08Reshaping and pivoting data5 lessons · 13 min

   1. Cross Tabulation2:08
   2. Pivoting3:39
   3. Wide to long and back7:05
   4. AssignmentAssignment
   5. Assignment SolutionAssignment
9. 09Combining dataframes6 lessons · 13 min

   1. Joining Dataframes3:35
   2. Types of Joins6:18
   3. Concatenating Dataframes2:29
   4. Course Review1:00
   5. AssignmentAssignment
   6. Assignment SolutionAssignment
10. 10Data cleaning and transformations6 lessons · 17 min

    1. Representing Missing Values5:06
    2. Threshold Based Dropping2:18
    3. Approaches To Filling Missing Data4:18
    4. Interpolation5:38
    5. AssignmentAssignment
    6. Assignment SolutionAssignment
11. 11Practical tips and tricks12 lessons · 35 min

    1. Compressed File Formats3:54
    2. Sparse Datatype2:52
    3. Combining Categories3:16
    4. Split Contents of a Column1:17
    5. Insert Column at Specific Location2:27
    6. Select using both Position and Lab3:55
    7. Styling Dataframes2:05
    8. Comprehensive Profile Report3:58
    9. Interactive Plots1:44
    10. Third Party Data4:09
    11. Interactive Data Analysis4:46
    12. Course Review1:00
12. 12Optimizing dataframes1 lesson · 8 min

    1. Optimizing Dataframes7:57
13. 13Handling Large Data6 lessons · 24 min

    1. Sampling On Load4:00
    2. Efficient File Formats2:26
    3. HDF56:13
    4. Chunking4:17
    5. Load to Database5:41
    6. Course Review1:00
14. 14Making Pandas Faster10 lessons · 1 h 3 min

    1. Faster Pandas0:49
    2. Numba7:07
    3. Dask Part-16:50
    4. Dask Part-24:37
    5. Modin6:14
    6. Swifter5:27
    7. Vaex12:33
    8. Cython6:59
    9. Cythonize Pandas Code6:06
    10. Cythonize apply5:54
15. 15Data Visualization12 lessons · 55 min

    1. Matplotlib Part 1 - Getting Started6:44
    2. Matplotlib Part 2 - Plot Components7:08
    3. Matplotlib Part 3 - Subplots7:02
    4. Matplotlib Part 4 - Annotations4:33
    5. Dual Axis Line Plots7:15
    6. Bar Charts6:01
    7. Histogram and Density Plots2:29
    8. Regression Plots6:22
    9. Pair Plots6:52
    10. Course Review1:00
    11. AssignmentAssignment
    12. Assignment SolutionAssignment
16. 16Course resources1 lesson · 1 min

    1. References and Next Step1:00

What you need

• No pre-requisites - Course is designed for absolute beginner

Who this course is for

• Data Science Beginners
• Aspirants/Practitioners who want to add Python in their skill-set

Your instructor

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

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