pandas Code Challenges

pandas Code Challenges

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 23m | 255 MB

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.

Table of Contents

1 Stretch and test your knowledge with pandas code challenges
2 What you should know

Reading and Initial Exploration of Data
3 Read data from CSV and Excel files
4 Check DataFrame information and identify types of columns
5 The summary statistics of numerical and categorical features
6 Add new columns to a DataFrame

Indexing and Slicing
7 Select specific columns in a DataFrame
8 Subset the data from labels using .loc[] method
9 Subset the data from indexing using .iloc[] method

Data Cleaning
10 Check for missing values
11 Correct the data type of a column
12 Parse dates in time series data

Filtering Data
13 Write conditional statements to filter rows
14 Chain multiple conditionals to narrow down the search
15 Using bitwise operators to filter rows
16 Filtering to find target demography

Grouping and Aggregation
17 Apply the three-step process to group and aggregate data
18 Group and aggregate multiple columns
19 Apply a custom aggregate function
20 Calculate stock returns for every year since 2003