pandas Code Challenges

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Harshit Tyagi

1:23:33

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01 - Introduction

01 - Stretch and test your knowledge with pandas code challenges.mp4

01:12

02 - What you should know.mp4

01:52

02 - 1. Reading and Initial Exploration of Data

01 - Read data from CSV and Excel files.mp4

04:00

02 - Check DataFrame information and identify types of columns.mp4

03:32

03 - The summary statistics of numerical and categorical features.mp4

04:03

04 - Add new columns to a DataFrame.mp4

03:50

03 - 2. Indexing and Slicing

01 - Select specific columns in a DataFrame.mp4

04:27

02 - Subset the data from labels using .loc[] method.mp4

05:17

03 - Subset the data from indexing using .iloc[] method.mp4

03:15

04 - 3. Data Cleaning

01 - Check for missing values.mp4

07:13

02 - Correct the data type of a column.mp4

05:34

03 - Parse dates in time series data.mp4

07:39

05 - 4. Filtering Data

01 - Write conditional statements to filter rows.mp4

02:10

02 - Chain multiple conditionals to narrow down the search.mp4

04:16

03 - Using bitwise operators to filter rows.mp4

03:51

04 - Filtering to find target demography.mp4

04:18

06 - 5. Grouping and Aggregation

01 - Apply the three-step process to group and aggregate data.mp4

04:04

02 - Group and aggregate multiple columns.mp4

02:43

03 - Apply a custom aggregate function.mp4

04:47

04 - Calculate stock returns for every year since 2003.mp4

05:30

Description

Want to test your pandas skills? These concise challenges let you stretch your brain and test your talents. Instructor Harshit Tyagi shares over a dozen pandas challenges, as well as his own solutions to each problem. Harshit’s challenges cover: Reading files and initial exploration of data using pandas attributes; data cleaning; creating subsets of data using indexing and slicing; writing queries to filter out rows based on conditional statements and Boolean indexing; and grouping and aggregation to answer categorical questions. Learn to apply statistical functions to groups. And since each challenge is self-contained, you can complete the course in any order—and at your own pace. Tune in to get the hands-on practice you need to keep your skills sharp.

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Pandas

Harshit Tyagi

Instructor's Courses

- An engineer with amalgamated experience in web technologies and data science(aka full-stack data science). - Mentored over 10K AI/Web/Data Science aspirants. - Designing data science, data engineering and ML engineering learning tracks. - Previously, developed data processing algorithms with research scientists at Yale, MIT, and UCLA.

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