https://github.com/mrankitgupta/python-libraries-roadmap

I am sharing lessons in various Python Libraries from scratch to intermediate including practice sets which were useful into my journey of Data Science.
https://github.com/mrankitgupta/python-libraries-roadmap

66daysofdata ai analytics ankitgupta artificial-intelligence data-science data-visualization libraries library machine-learning matplotlib mrankitgupta numpy pandas python python-libraries python-library pythonlib scikit-learn tensorflow

Last synced: 8 months ago
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I am sharing lessons in various Python Libraries from scratch to intermediate including practice sets which were useful into my journey of Data Science.

Host: GitHub
URL: https://github.com/mrankitgupta/python-libraries-roadmap
Owner: mrankitgupta
License: mit
Created: 2022-03-06T18:39:17.000Z (almost 4 years ago)
Default Branch: main
Last Pushed: 2022-11-16T07:00:58.000Z (about 3 years ago)
Last Synced: 2025-03-29T19:11:18.318Z (9 months ago)
Topics: 66daysofdata, ai, analytics, ankitgupta, artificial-intelligence, data-science, data-visualization, libraries, library, machine-learning, matplotlib, mrankitgupta, numpy, pandas, python, python-libraries, python-library, pythonlib, scikit-learn, tensorflow
Language: Python
Homepage:
Size: 27.3 KB
Stars: 8
Watchers: 2
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

          
Python Libraries for Data Analysis and Data Science Roadmap    


**I am sharing lessons in various Python Libraries from scratch to intermediate including practice sets which were useful into my journey of Data Science.** 

For more detials, refer: [Data Analyst Roadmap](https://github.com/mrankitgupta/Data-Analyst-Roadmap) :hourglass: & [Python Roadmap](https://github.com/mrankitgupta/Python-Roadmap) 📑

### Overview of Python Libraries

Python libraries are pre-written programs that allow developers to program more efficiently. They are easy to use and can be found in many different frameworks. These libraries provide an API (application programming interface) which makes it easy for developers to use them with their own software programs.

Python libraries are a great way to data analysis and machine learning. They provide powerful functionality and flexibility for any task, regardless of the type of data. Python libraries make it easy for developers and data scientists to prototype and scale their models, regardless of their size or complexity.

The Python programming language comes with a built-in library called the “Standard Library” which has all the necessary modules for tasks like input/output, data manipulation, text processing, packaging, and more.

Making use of the Python Standard Library is not enough for many developers because it cannot accommodate all their needs. That is why there are also Python Libraries that can be imported in order to make them more efficient when accomplishing specific tasks.

## Technologies used ⚙️

* Python   

* Statistics  

##### Python Libraries : 

* Pandas   

* NumPy   

* Matplotlib   

* Seaborn   

Certifications 📜 🎓 ✔️


- [Data Analysis with Python](https://github.com/mrankitgupta) - by IBM

 

- [Data Visualization with Python](https://github.com/mrankitgupta) - by IBM

- [Pandas](https://www.kaggle.com/learn/certification/mrankitgupta/pandas) - by Kaggle

 

- [Numpy](https://olympus1.mygreatlearning.com/course_certificate/IQVNJSIN) - by Great Learning 

- [Matplotlib](https://olympus1.mygreatlearning.com/course_certificate/RNVTUIMW) - by Great Learning

- [Databases and SQL for Data Science with Python](https://github.com/mrankitgupta) - by IBM

- [Statistics for Data Science with Python](https://www.credly.com/badges/354576a0-b672-4245-8cad-82dc3f3df76f/public_url) - by IBM

## Featured projects:question: 👨‍💻 🛰️

[Data Analyst Roadmap](https://github.com/mrankitgupta/Data-Analyst-Roadmap) :hourglass: 

[Spotify Data Analysis using Python](https://github.com/mrankitgupta/Spotify-Data-Analysis-using-Python) 📊

[Sales Insights - Data Analysis using Tableau & SQL](https://github.com/mrankitgupta/Sales-Insights-Data-Analysis-using-Tableau-and-SQL) 📊

[Statistics for Data Science using Python](https://github.com/mrankitgupta/Statistics-for-Data-Science-using-Python) 📊

 

[Kaggle - Pandas Solved Exercises](https://github.com/mrankitgupta/Kaggle-Pandas-Solved-Exercises) 📊

 

[Complete Python Roadmap](https://github.com/mrankitgupta/Python-Roadmap) 📑

 

## Python Libraries for Data Analysis and Data Science   

Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks more quickly and efficiently.

There are many different libraries in Python, which provide useful data analysis tools for scientists and engineers.These libraries can be used to analyze, graph and visualize data. They can also be used to create complex mathematical equations and 3D animations.

**Prerequisite:** [Complete Python Roadmap](https://github.com/mrankitgupta/Python-Roadmap) 📑 

Python has a number of libraries, like :

 Pandas   


|**Sr.No. 🔢**|**Pandas Lessons 📕**| **Reference Links :link:**| **Exercises 👨‍💻**|

|------|--------------------|---------------------|---------------------|

|1| Basics, Data Structures - Series, DataFrame, Panel | [Pandas Course - by Kaggle](https://www.kaggle.com/learn/certification/mrankitgupta/pandas) | [Exercise 1](https://www.kaggle.com/code/mrankitgupta/pandas-1-exercise-creating-reading-and-writing/notebook) |

|2| **Summary Functions and Maps, Operations** - Slicing, Merging | [Kaggle Notebooks on Pandas](https://www.kaggle.com/mrankitgupta/code) | [Exercise 2](https://www.kaggle.com/code/mrankitgupta/pandas-2exercise-indexing-selecting-assigning) |

|3| **Operations** - Joining, Concatenation | [GitHub Repo on Pandas](https://github.com/mrankitgupta/Kaggle-Pandas-Solved-Exercises) | [Exercise 3](https://www.kaggle.com/code/mrankitgupta/pandas-3-exercise-summary-functions-and-maps) |

|4| Changing Index & Column Header, Data Munging | [JavaTpoint](https://www.javatpoint.com/python-pandas)| [Exercise 4](https://www.kaggle.com/code/mrankitgupta/pandas-4-exercise-grouping-and-sorting) |

|5| Grouping & Sorting, Data Types & Missing Values | [YouTube](https://www.youtube.com/watch?v=WGJJIrtnfpk&t=30498s)| [Exercise 5](https://www.kaggle.com/code/mrankitgupta/pandas-5-exercise-data-types-and-missing-values) |

|6| Renaming and Combining | [TutorialsPoint](https://www.tutorialspoint.com/python_pandas/index.htm)| [Exercise 6](https://www.kaggle.com/code/mrankitgupta/pandas-6-exercise-renaming-and-combining) |

|7| Pandas-Matplotlib | :white_check_mark:| |

  

 NumPy   

 

 

|**Sr.No. 🔢**|**NumPy Lessons 📕**| **Reference Links :link:**| **Exercises 👨‍💻**|

|------|--------------------|---------------------|---------------------|

|1| Basics, NumPy v/s MATLAB, NumPy v/s List, NdArray, Datatypes, Array Attributes | [NumPy Tutorial - by Great Learning](https://olympus1.mygreatlearning.com/course_certificate/IQVNJSIN)| [Exercise 1](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%201%20-%20NdArray) |

|2| NdArray, Datatypes, Array Attributes | [JavaTpoint](https://www.javatpoint.com/numpy-tutorial)| [Exercise 2](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%202%20-%20Indexing%20%26%20Slicing) |

|3| Indexing & Slicing, Array Creation | [YouTube](https://www.youtube.com/watch?v=WGJJIrtnfpk&t=27503s), [TutorialsPoint](https://www.tutorialspoint.com/numpy/index.htm) | [Exercise 3](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%203%20-%20NumPy%20Broadcasting) |

|4| Broadcasting, Operations, Functions | [TutorialsPoint](https://www.tutorialspoint.com/numpy/index.htm) | [Exercise 4](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%204%20-%20NumPy%20Operations) |

|5| Mathematics, Matrix, NumPy-Matplotlib | :white_check_mark:| [Exercise 5](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%205%20-%20NumPy%20Matrix) & [Exercise 6](https://github.com/mrankitgupta/Python-Libraries/tree/main/Numpy%20Exercises/Exercise%206%20-%20NumPy-Matplotlib) |

 Matplotlib   


|**Sr.No. 🔢**|**Matplotlib Lessons 📕**| **Reference Links :link:**| **Exercises 👨‍💻**|

|------|--------------------|---------------------|---------------------|

|1| Basics, Data Visualization, Architecture, Concepts | [Matplotlib Course - by Great Learning](https://olympus1.mygreatlearning.com/course_certificate/RNVTUIMW)| [Exercise 1](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%201%20-%20Line%20Graph) |

|2| Pyplot & Subplot | [JavaTpoint](https://www.javatpoint.com/matplotlib) | [Exercise 2](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%202%20-%20Bar%20Graph) |

|3| 7 Types of plots | [YouTube](https://www.youtube.com/watch?v=WGJJIrtnfpk&t=32953s)| [Exercise 3](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%203%20-%20Histogram) & [Exercise 4](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%204%20-%20Pie%20Chart) |

|4| Multiple plots | [TutorialsPoint](https://www.tutorialspoint.com/matplotlib/index.htm) :white_check_mark:| [Exercise 5](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%205%20-%20Scatter%20Plot) & [Exercise 6](https://github.com/mrankitgupta/Python-Libraries/tree/main/Matplotlib%20Exercises/Exercise%206%20-%203D%20Plot) |

 Seaborn   


|**Sr.No. 🔢**|**Seaborn Lessons 📕**| **Reference Links :link:**|

|------|--------------------|---------------------|

|1| Style functions | [YouTube](https://www.youtube.com/watch?v=WGJJIrtnfpk&t=34338s) |

|2| Color palettes | [TutorialsPoint](https://www.tutorialspoint.com/seaborn/index.htm) |

|2| Distribution plots | [JavaTpoint](https://www.javatpoint.com/python-seaborn-library) |

|2| Categorical plots |  |

|2| Regression plots |  |

|3| Axis grid objects | :white_check_mark:|

### Projects in Python

|**Sr.No. 🔢**|**Projects 👨‍💻**| **Reference Links :link:**|

|------|--------------------|---------------------|

|**Python Project 1**| Spotify Data Analysis using Python | [GitHub Project](https://github.com/mrankitgupta/Spotify-Data-Analysis-using-Python) & [Kaggle Notebook](https://www.kaggle.com/code/mrankitgupta/spotify-data-analysis-using-python-project) |

|**Python Project 2**| Boston Housing Data Analysis using Python | [Project](https://github.com/mrankitgupta/Statistics-for-Data-Science-using-Python-Project) |

## Useful sites to learn Coding in Python  :link:

### YouTube Channels:

| [freeCodeCamp.org](https://www.youtube.com/channel/UC8butISFwT-Wl7EV0hUK0BQ) | [Code With Harry](https://www.youtube.com/channel/UCeVMnSShP_Iviwkknt83cww), [Programming With Harry](https://www.youtube.com/channel/UC7btqG2Ww0_2LwuQxpvo2HQ) | [CodeBasics](https://www.youtube.com/c/codebasics) | [Edureka](https://www.youtube.com/channel/UCkw4JCwteGrDHIsyIIKo4tQ) | [Gate Smashers](https://www.youtube.com/c/GateSmashers) | [Jenny's Lectures](https://www.youtube.com/c/JennyslecturesCSITNETJRF) | [Simplilearn](https://www.youtube.com/channel/UCsvqVGtbbyHaMoevxPAq9Fg) | [Intellipaat](https://www.youtube.com/c/Intellipaat) |

|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|

### Other Learning Platforms:

| [JavaTpoint](https://www.javatpoint.com/) | [TutorialsPoint](https://www.tutorialspoint.com/tutorialslibrary.htm) | [Geeks For Geeks](https://www.geeksforgeeks.org/) | [Code With Harry](https://www.codewithharry.com/) | [GitHub](https://github.com/mrankitgupta) | [Kaggle](https://www.kaggle.com/mrankitgupta) | [DataCamp](https://www.datacamp.com/) | [W3Schools](https://www.w3schools.com/) | [Guru99](https://www.guru99.com/) | [Dev](https://dev.to/mrankitgupta) |

|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|

 

### For Certifications:

| [Coursera](https://coursera.org/share/c40b8f3c3c8ef8195d4dbfe8b2528f4d) | [Kaggle](https://www.kaggle.com/learn/certification/mrankitgupta/pandas) | [Simplilearn](https://www.simplilearn.com/skillup-certificate-landing?token=eyJjb3Vyc2VfaWQiOiI3OTUiLCJjZXJ0aWZpY2F0ZV91cmwiOiJodHRwczpcL1wvY2VydGlmaWNhdGVzLnNpbXBsaWNkbi5uZXRcL3NoYXJlXC90aHVtYl8zMzkyNjI4XzE2NTAxMTE0NzcucG5nIiwidXNlcm5hbWUiOiJBbmtpdCBHdXB0YSJ9&utm_source=shared-certificate&utm_medium=lms&utm_campaign=shared-certificate-promotion) | [Great Learnings](https://olympus1.mygreatlearning.com/course_certificate/IQVNJSIN) | [Forage](https://www.theforage.com/) | [Edureka](https://www.edureka.co/) | [HackerRank](https://www.hackerrank.com/mrankitgupta)  | [Udemy](https://www.udemy.com/) | [Codechef](https://www.codechef.com/)  | [Upgrad](https://www.upgrad.com/) | [Udacity](https://www.udacity.com/) |

|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|

### For Coding Practice:

| [HackerRank](https://www.hackerrank.com/mrankitgupta) | [Leetcode](https://leetcode.com/mrankitgupta1/) | [Kaggle](https://www.kaggle.com/mrankitgupta) | [Codechef](https://www.codechef.com/) | [Unstop](https://unstop.com/) | [HackerEarth](https://www.hackerearth.com/practice/) | [Codeforces](https://codeforces.com/) | [Interviewbit](https://www.interviewbit.com/) | [Google Dev](https://developers.google.com/) |

|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|--------------------|

### Liked my Contributions:question:[Follow Me](https://github.com/mrankitgupta/):point_right: [Nominate Me for GitHub Stars](https://stars.github.com/nominate/) :star: :sparkles:

## For any queries/doubts 🔗 👇 

### [Ankit Gupta](https://bio.link/AnkitGupta)