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[ CourseMega.com ] Pandas In Action, Video Edition
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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 technology
Data analysis with Python doesn’t have to be hard. If you can use a spreadsheet, you can learn pandas! While its grid-style layouts may remind you of Excel, pandas is far more flexible and powerful. This Python library quickly performs operations on millions of rows, and it interfaces easily with other tools in the Python data ecosystem. It’s a perfect way to up your data game.
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FILE LIST
Filename
Size
~Get Your Files Here !/01-Part 1. Core pandas.mp4
4.6 MB
~Get Your Files Here !/02-Chapter 1. Introducing pandas.mp4
57.1 MB
~Get Your Files Here !/03-Chapter 1. Pandas vs. graphical spreadsheet applications.mp4
77.6 MB
~Get Your Files Here !/04-Chapter 1. A tour of pandas.mp4
35.7 MB
~Get Your Files Here !/05-Chapter 1. Counting values in a Series.mp4
38.7 MB
~Get Your Files Here !/06-Chapter 2. The Series object.mp4
36.5 MB
~Get Your Files Here !/07-Chapter 2. Customizing the Series index.mp4
31.9 MB
~Get Your Files Here !/08-Chapter 2. Creating a Series from Python objects.mp4
31.4 MB
~Get Your Files Here !/09-Chapter 2. Mathematical operations.mp4
45.4 MB
~Get Your Files Here !/10-Chapter 2. Arithmetic operations.mp4
19.2 MB
~Get Your Files Here !/11-Chapter 2. Passing the Series to Python’s built-in functions.mp4
27 MB
~Get Your Files Here !/12-Chapter 3. Series methods.mp4
43.5 MB
~Get Your Files Here !/13-Chapter 3. Sorting a Series.mp4
31.4 MB
~Get Your Files Here !/14-Chapter 3. Counting values with the value_counts method.mp4
27.1 MB
~Get Your Files Here !/15-Chapter 3. Invoking a function on every Series value with the apply method.mp4
36.8 MB
~Get Your Files Here !/16-Chapter 4. The DataFrame object.mp4
32.4 MB
~Get Your Files Here !/17-Chapter 4. Shared and exclusive attributes of Series and DataFrames.mp4
24.5 MB
~Get Your Files Here !/18-Chapter 4. Sorting a DataFrame.mp4
49.2 MB
~Get Your Files Here !/19-Chapter 4. Selecting rows from a DataFrame.mp4
33.3 MB
~Get Your Files Here !/20-Chapter 4. Extracting values from Series.mp4
41.6 MB
~Get Your Files Here !/21-Chapter 5. Filtering a DataFrame.mp4
42.6 MB
~Get Your Files Here !/22-Chapter 5. Filtering by a single condition.mp4
37.6 MB
~Get Your Files Here !/23-Chapter 5. Filtering by condition.mp4
41.6 MB
~Get Your Files Here !/24-Chapter 5. The drop_duplicates method.mp4
59.4 MB
~Get Your Files Here !/25-Part 2. Applied pandas.mp4
13.9 MB
~Get Your Files Here !/26-Chapter 6. Working with text data.mp4
25.5 MB
~Get Your Files Here !/27-Chapter 6. String slicing.mp4
27.5 MB
~Get Your Files Here !/28-Chapter 6. Splitting strings.mp4
41.7 MB
~Get Your Files Here !/29-Chapter 7. MultiIndex DataFrames.mp4
31.9 MB
~Get Your Files Here !/30-Chapter 7. MultiIndex DataFrames - Scaling up.mp4
34.2 MB
~Get Your Files Here !/31-Chapter 7. Sorting a MultiIndex.mp4
37.4 MB
~Get Your Files Here !/32-Chapter 7. Extracting one or more rows with loc.mp4
40.2 MB
~Get Your Files Here !/33-Chapter 7. Manipulating the Index.mp4
41.9 MB
~Get Your Files Here !/34-Chapter 8. Reshaping and pivoting.mp4
57.2 MB
~Get Your Files Here !/35-Chapter 8. Additional options for pivot tables.mp4
29.4 MB
~Get Your Files Here !/36-Chapter 8. Melting a data set.mp4
45.4 MB
~Get Your Files Here !/37-Chapter 9. The GroupBy object.mp4
27.4 MB
~Get Your Files Here !/38-Chapter 9. Attributes and methods of a GroupBy object.mp4
47.2 MB
~Get Your Files Here !/39-Chapter 9. Grouping by multiple columns.mp4
29.9 MB
~Get Your Files Here !/40-Chapter 10. Merging, joining, and concatenating.mp4
46.8 MB
~Get Your Files Here !/41-Chapter 10. Missing values in concatenated DataFrames.mp4
45.8 MB
~Get Your Files Here !/42-Chapter 10. Merging on index labels.mp4
36.3 MB
~Get Your Files Here !/43-Chapter 11. Working with dates and times.mp4
34.7 MB
~Get Your Files Here !/44-Chapter 11. Storing multiple timestamps in a DatetimeIndex.mp4
37.8 MB
~Get Your Files Here !/45-Chapter 11. Date offsets.mp4
34.9 MB
~Get Your Files Here !/46-Chapter 11. Coding challenge.mp4
45.4 MB
~Get Your Files Here !/47-Chapter 12. Imports and exports.mp4
46.4 MB
~Get Your Files Here !/48-Chapter 12. Exporting a DataFrame to a JSON file.mp4
41.4 MB
~Get Your Files Here !/49-Chapter 12. Exporting Excel workbooks.mp4
32.4 MB
~Get Your Files Here !/50-Chapter 13. Configuring pandas.mp4
32.6 MB
~Get Your Files Here !/51-Chapter 13. Precision.mp4
27.8 MB
~Get Your Files Here !/52-Chapter 14. Visualization.mp4
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