Skip to content
/ teaching-data-science Public

Repository that includes Jupyter Notebooks covering essential concepts and hands-on exercises for data analysis and data visualization using Pandas, Numpy, Matplotlib, and Seaborn. Whether you're a beginner or looking to refine your skills, this repo offers practical insights.

1 star 1 fork Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

andrelbd1/teaching-data-science

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

59 Commits
datasets
datasets
 
 
figures
figures
 
 
.gitignore
.gitignore
 
 
01. Series, DataFrame and Reindex.html
01. Series, DataFrame and Reindex.html
 
 
01. Series, DataFrame and Reindex.ipynb
01. Series, DataFrame and Reindex.ipynb
 
 
02. Apply, Applymap, Lambda, Sorting and Classification.html
02. Apply, Applymap, Lambda, Sorting and Classification.html
 
 
02. Apply, Applymap, Lambda, Sorting and Classification.ipynb
02. Apply, Applymap, Lambda, Sorting and Classification.ipynb
 
 
03. Indexing, Merge, Concatenate, and Combine.html
03. Indexing, Merge, Concatenate, and Combine.html
 
 
03. Indexing, Merge, Concatenate, and Combine.ipynb
03. Indexing, Merge, Concatenate, and Combine.ipynb
 
 
04. Aggregation.html
04. Aggregation.html
 
 
04. Aggregation.ipynb
04. Aggregation.ipynb
 
 
05. Matplotlib.html
05. Matplotlib.html
 
 
05. Matplotlib.ipynb
05. Matplotlib.ipynb
 
 
06. Statistical Analysis.html
06. Statistical Analysis.html
 
 
06. Statistical Analysis.ipynb
06. Statistical Analysis.ipynb
 
 
07. Data Normalization and Standardization.html
07. Data Normalization and Standardization.html
 
 
07. Data Normalization and Standardization.ipynb
07. Data Normalization and Standardization.ipynb
 
 
08. Data Cleaning.html
08. Data Cleaning.html
 
 
08. Data Cleaning.ipynb
08. Data Cleaning.ipynb
 
 
09. Practice - Titanic.html
09. Practice - Titanic.html
 
 
09. Practice - Titanic.ipynb
09. Practice - Titanic.ipynb
 
 
10. Practice - IMDb.html
10. Practice - IMDb.html
 
 
10. Practice - IMDb.ipynb
10. Practice - IMDb.ipynb
 
 
11. Practice - Consumers Complaints.html
11. Practice - Consumers Complaints.html
 
 
11. Practice - Consumers Complaints.ipynb
11. Practice - Consumers Complaints.ipynb
 
 
12. Practice - Time Series Forecasting using Decision Tree and Gradient Boosting.html
12. Practice - Time Series Forecasting using Decision Tree and Gradient Boosting.html
 
 
12. Practice - Time Series Forecasting using Decision Tree and Gradient Boosting.ipynb
12. Practice - Time Series Forecasting using Decision Tree and Gradient Boosting.ipynb
 
 
README.md
README.md
 
 
requirements.txt
requirements.txt
 
 

Repository files navigation

Teaching Data Science

GitHub last commit GitHub repo size in bytes

Quick Setup

Create a virtualenv and install the requirements.

    virtualenv venv
    source venv/bin/activate
    pip install -r requirements.txt

Hands on:

Data Visualization:

About

Repository that includes Jupyter Notebooks covering essential concepts and hands-on exercises for data analysis and data visualization using Pandas, Numpy, Matplotlib, and Seaborn. Whether you're a beginner or looking to refine your skills, this repo offers practical insights.

Topics

python data-science numpy jupyter-notebook pandas data-visualization seaborn matplotlib

Resources

Readme
Activity

Stars

1 star

Watchers

2 watching

Forks

1 fork
Report repository

Contributors 2

  •  
  •  

Languages