Python Pandas Full Course (2024)

Free Download Python Pandas Full Course (2024)
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.06 GB | Duration: 5h 51m
Learn Pandas with 100+ hands-on live running coding examples and exercises

What you'll learn
Learn Pandas from scratch (2024)
Learn Pandas for Data Science and Data Analysis
Acquire essential Pandas skills
Practice your skills with 100+ coding exercises
Learn Pandas best practices
Be able to program in Pandas professionally.
Learn to read CSV and Excel files with ease in Python
Requirements
A computer with an Internet
Python knowledge
Passion to learn Pandas
Description
Welcome to the Pandas Course for Beginners by Studyopedia.Pandas is a powerful and easy-to-use open-source tool built on top of the Python programming language. It is useful for data analysis and manipulation. Python with pandas is widely used in Statistics, Finance, Neuroscience, Economics, Web Analytics, Advertising, etc.To work with data sets, clean them, and make them relevant for Data Science is what Pandas do. With that, easily load and read data sets in Excel, CSV, JSON, XML, etc. formats with Pandas and work on them. Easily clean the wrong format data, remove duplicates, and do other tasks with Pandas.FeaturesAnalyze DataManipulate DataColumns can be inserted and deleted from DataFrameGroup the rows/ columns of a DataFrame/ SeriesPlotting is possibleRead CSV/ JSONFix the inaccurate dataClean the Data completelyEasy to handle the missing data in the form: NaN, NA, or NaTCourse Lessons1. Pandas – Introduction & Features2. Install & Setup Pandas3. Create a Pandas DataFrame (Run first program)4. Pandas DataFrames – Attributes & Methods5. Join Pandas DataFrame6. Concatenate Pandas DataFrames7. Create a Pandas Series8. Pandas Series – Attributes & Methods9. Combine two Pandas series10. Categorical Data in Pandas11. Working with Categories in Pandas12. Read CSV in Pandas13. Read Excel in Pandas14. Indexing in Pandas15. Select multiple columns in Pandas16. Add a new column in Pandas17. Delete rows/ columns in Pandas18. Iterate over rows and columns in Pandas19. Sorting in Pandas20. Handle Duplicates in Pandas21. Clean the Data in Pandas22. String Operations in Pandas23. Date Time Operations in Pandas24. Remove Whitespace in Pandas25. Group the Data in Pandas26. Statistical Functions in Pandas27. Plot a DataFrame in PandasHit the Enroll button!
Overview
Section 1: Pandas - Introduction & Setup
Lecture 1 Pandas Introduction & Features
Lecture 2 Pandas Installation & Setup
Section 2: Pandas - DataFrames
Lecture 3 Create a DataFrame (Run First Pandas Program)
Lecture 4 DataFrame - Attributes and Methods
Lecture 5 Join DataFrames
Lecture 6 Concatenate DataFrames
Section 3: Pandas - Series
Lecture 7 Create a Series
Lecture 8 Series - Attributes and Methods
Lecture 9 Combine two Series
Section 4: Pandas - Categorical
Lecture 10 Categorical Data
Lecture 11 Working with Categories
Section 5: Pandas - Read CSV, Excel
Lecture 12 Read CSV
Lecture 13 Read Excel
Section 6: Pandas - Indexing and Selecting
Lecture 14 Indexing
Lecture 15 Select multiple columns
Section 7: Pandas - Data Manipulation
Lecture 16 Add a new column
Lecture 17 Delete rows/ columns
Lecture 18 Iterate over rows and columns
Lecture 19 Sorting
Section 8: Pandas - Data Cleaning
Lecture 20 Handle Duplicates
Lecture 21 Clean the Data
Section 9: Pandas - Operations
Lecture 22 String Operations
Lecture 23 Date Time Operations
Lecture 24 Remove Whitespace & special characters
Lecture 25 Group the Data
Lecture 26 Statistical Functions
Section 10: Pandas - Plotting
Lecture 27 Plotting in Pandas
Those who want to learn Pandas by doing. This course includes 50+ hands-on exercises,Gain a deep understanding of Python Pandas,Python Libraries Beginners,Get started with Pandas,Learn all the topics in Pandas

Homepage

https://www.udemy.com/course/python-pandas-full-course/

No Password - Links are Interchangeable

Вернуться назад

Навигация

Рекомендуем

Статистика

Python Pandas Full Course (2024)

Коментарии

Рекомендуем

Популярное