| 0 | 452.1 KB | ||
| 01-Part 1. Core pandas.mp4 | 4.6 MB | ||
| 02-Chapter 1. Introducing pandas.mp4 | 57.1 MB | ||
| 03-Chapter 1. Pandas vs. graphical spreadsheet applications.mp4 | 77.6 MB | ||
| 04-Chapter 1. A tour of pandas.mp4 | 35.7 MB | ||
| 05-Chapter 1. Counting values in a Series.mp4 | 38.7 MB | ||
| 06-Chapter 2. The Series object.mp4 | 36.5 MB | ||
| 07-Chapter 2. Customizing the Series index.mp4 | 31.9 MB | ||
| 08-Chapter 2. Creating a Series from Python objects.mp4 | 31.4 MB | ||
| 09-Chapter 2. Mathematical operations.mp4 | 45.4 MB | ||
| 10-Chapter 2. Arithmetic operations.mp4 | 19.2 MB | ||
| 11-Chapter 2. Passing the Series to Python’s built-in functions.mp4 | 27 MB | ||
| 12-Chapter 3. Series methods.mp4 | 43.5 MB | ||
| 13-Chapter 3. Sorting a Series.mp4 | 31.4 MB | ||
| 14-Chapter 3. Counting values with the value_counts method.mp4 | 27.1 MB | ||
| 15-Chapter 3. Invoking a function on every Series value with the apply method.mp4 | 36.8 MB | ||
| 16-Chapter 4. The DataFrame object.mp4 | 32.4 MB | ||
| 17-Chapter 4. Shared and exclusive attributes of Series and DataFrames.mp4 | 24.5 MB | ||
| 18-Chapter 4. Sorting a DataFrame.mp4 | 49.2 MB | ||
| 19-Chapter 4. Selecting rows from a DataFrame.mp4 | 33.3 MB | ||
| 20-Chapter 4. Extracting values from Series.mp4 | 41.6 MB | ||
| 21-Chapter 5. Filtering a DataFrame.mp4 | 42.6 MB | ||
| 22-Chapter 5. Filtering by a single condition.mp4 | 37.6 MB | ||
| 23-Chapter 5. Filtering by condition.mp4 | 41.6 MB | ||
| 24-Chapter 5. The drop_duplicates method.mp4 | 59.4 MB | ||
| 25-Part 2. Applied pandas.mp4 | 13.9 MB | ||
| 26-Chapter 6. Working with text data.mp4 | 25.5 MB | ||
| 27-Chapter 6. String slicing.mp4 | 27.5 MB | ||
| 28-Chapter 6. Splitting strings.mp4 | 41.7 MB | ||
| 29-Chapter 7. MultiIndex DataFrames.mp4 | 31.9 MB | ||
| 30-Chapter 7. MultiIndex DataFrames - Scaling up.mp4 | 34.2 MB | ||
| 31-Chapter 7. Sorting a MultiIndex.mp4 | 37.4 MB | ||
| 32-Chapter 7. Extracting one or more rows with loc.mp4 | 40.2 MB | ||
| 33-Chapter 7. Manipulating the Index.mp4 | 41.9 MB | ||
| 34-Chapter 8. Reshaping and pivoting.mp4 | 57.2 MB | ||
| 35-Chapter 8. Additional options for pivot tables.mp4 | 29.4 MB | ||
| 36-Chapter 8. Melting a data set.mp4 | 45.4 MB | ||
| 37-Chapter 9. The GroupBy object.mp4 | 27.4 MB | ||
| 38-Chapter 9. Attributes and methods of a GroupBy object.mp4 | 47.2 MB | ||
| 39-Chapter 9. Grouping by multiple columns.mp4 | 29.9 MB | ||
| 40-Chapter 10. Merging, joining, and concatenating.mp4 | 46.8 MB | ||
| 41-Chapter 10. Missing values in concatenated DataFrames.mp4 | 45.8 MB | ||
| 42-Chapter 10. Merging on index labels.mp4 | 36.3 MB | ||
| 43-Chapter 11. Working with dates and times.mp4 | 34.7 MB | ||
| 44-Chapter 11. Storing multiple timestamps in a DatetimeIndex.mp4 | 37.8 MB | ||
| 45-Chapter 11. Date offsets.mp4 | 34.9 MB | ||
| 46-Chapter 11. Coding challenge.mp4 | 45.4 MB | ||
| 47-Chapter 12. Imports and exports.mp4 | 46.4 MB | ||
| 48-Chapter 12. Exporting a DataFrame to a JSON file.mp4 | 41.4 MB | ||
| 49-Chapter 12. Exporting Excel workbooks.mp4 | 32.4 MB | ||
| 50-Chapter 13. Configuring pandas.mp4 | 32.6 MB | ||
| 51-Chapter 13. Precision.mp4 | 27.8 MB | ||
| 52-Chapter 14. Visualization.mp4 | 40.6 MB | ||
| TutsNode.com.txt | 102.4 B | ||
| [TGx]Downloaded from torrentgalaxy.to .txt | 614.4 B | ||
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Description
Take the next steps in your data science career! This friendly and hands-on guide shows you how to start mastering Pandas with skills you already know from spreadsheet software.
In Pandas in Action you will learn
Import datasets, identify issues with their data structures, and optimize them for efficiency
Sort, filter, pivot, and draw conclusions from a dataset and its subsets
Identify trends from text-based and time-based data
Organize, group, merge, and join separate datasets
Use a GroupBy object to store multiple DataFrames
Pandas has rapidly become one of Python’s most popular data analysis libraries. In Pandas in Action, a friendly and example-rich introduction, author Boris Paskhaver shows you how to master this versatile tool and take the next steps in your data science career. You’ll learn how easy Pandas makes it to efficiently sort, analyze, filter and munge almost any type of data.
about the audience
For readers experienced with spreadsheets and basic Python programming.
Published 9/2021
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.4 GB | freecoursewb | 7 months | 3 | 0 | |
| 336.5 MB | xHOBBiTx | 2 years | 9 | 1 | |
| 2.2 GB | freecoursewb | 2 years | 0 | 0 | |
| 1.9 GB | freecoursewb | 4 years | 0 | 0 | |
| 2.4 GB | CourseClub | 4 years | 0 | 0 |
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