Python For DataScience

Hello! Welcome to my GitHub repository where I have covered four courses certificates:
Python for Data Science, AI & Development
Data Analysis using Python
Data Visualization with Python
Python Project for Data Science

About the Repository: This repository is a mix of resources I gathered during my learning phase. I have included materials from IBM Professional courses, various YouTube channels, blogs, official documentation, and also ChatGpt helped me a lot to understand code. I aimed to cover a wide range of topics related to data science and improve my knowledge in this field.

Continuous Improvement: As a dedicated learner, my commitment to enhancing my knowledge and skills in data science remains unwavering. I am devoted to regularly updating this repository with a wide range of topics, advanced analysis techniques, and innovative visualization methods as I progress on my learning journey. I highly value feedback and collaboration, so please feel free to reach out to me if you notice any mistakes or have suggestions for improvement. Your insights are greatly appreciated!

GitHub Engagement: I am thrilled to share that this repository has gained significant traction within just one month! It has received over 3,000 views and also many Clones.

Connect with Me: If you would like to connect with me professionally, please feel free to reach out on LinkedIn. You can find my profile here.

Thank you for visiting my GitHub repository, and I hope you find the resources and materials valuable for your data science journey!

Name		Name	Last commit message	Last commit date
Latest commit History 83 Commits
All Datasets		All Datasets
0- Python Fun Fact.ipynb		0- Python Fun Fact.ipynb
1- Python Basics.ipynb		1- Python Basics.ipynb
10- Pandas - Part 4.ipynb		10- Pandas - Part 4.ipynb
11- Pandas - Part 5.ipynb		11- Pandas - Part 5.ipynb
12- Pandas Data analysis - Part 6.ipynb		12- Pandas Data analysis - Part 6.ipynb
13- Pandas - IPL DeathOverBatsmenAnalysis - Part 7.ipynb		13- Pandas - IPL DeathOverBatsmenAnalysis - Part 7.ipynb
14- pandas - merge function part 8.ipynb		14- pandas - merge function part 8.ipynb
15- Pandas - Pivot Table.ipynb		15- Pandas - Pivot Table.ipynb
16- pandas correlation part 10.ipynb		16- pandas correlation part 10.ipynb
17- Pandas - rename() function part 11.ipynb		17- Pandas - rename() function part 11.ipynb
18- Pandas - set_index() and reset_index().ipynb		18- Pandas - set_index() and reset_index().ipynb
19- Pandas - dropna() method.ipynb		19- Pandas - dropna() method.ipynb
2- Python Control Flows - Loops.ipynb		2- Python Control Flows - Loops.ipynb
20- Pandas - fillna() method.ipynb		20- Pandas - fillna() method.ipynb
21- Pickling and Unpickling in Python.ipynb		21- Pickling and Unpickling in Python.ipynb
22- Data Wrangling - Part 1 Identifying Missing Data.ipynb		22- Data Wrangling - Part 1 Identifying Missing Data.ipynb
23- Data Wrangling - Part 2 Deal with missing data.ipynb		23- Data Wrangling - Part 2 Deal with missing data.ipynb
24- Data Wrangling - Part 3 Data Standardization and Normalization.ipynb		24- Data Wrangling - Part 3 Data Standardization and Normalization.ipynb
25- Data Wrangling - Part 4 Binning.ipynb		25- Data Wrangling - Part 4 Binning.ipynb
26- Data Wrangling - Part 5 Indicator Variable.ipynb		26- Data Wrangling - Part 5 Indicator Variable.ipynb
27- EDA - Part 1 Feature Visualization.ipynb		27- EDA - Part 1 Feature Visualization.ipynb
28- EDA - Part 2 Descriptive Stats and Grouping Basics.ipynb		28- EDA - Part 2 Descriptive Stats and Grouping Basics.ipynb
29- EDA - Part 3 CorrelationCausation and ANOVA.ipynb		29- EDA - Part 3 CorrelationCausation and ANOVA.ipynb
3- Python Operators.ipynb		3- Python Operators.ipynb
30- ModelDevelopment - part 1 Linear ML Regression.ipynb		30- ModelDevelopment - part 1 Linear ML Regression.ipynb
31- ModelDevelopment - part 2 ModelEval Visualization.ipynb		31- ModelDevelopment - part 2 ModelEval Visualization.ipynb
32- ModelDevelopment - part 3 Polynomial Reg and Pipelines.ipynb		32- ModelDevelopment - part 3 Polynomial Reg and Pipelines.ipynb
33- ModelDevelopment - part 4 Measures for In-Sample Evaluation.ipynb		33- ModelDevelopment - part 4 Measures for In-Sample Evaluation.ipynb
34- Model Evaluation part 1 .ipynb		34- Model Evaluation part 1 .ipynb
35- Model Evaluation part 2 Over-Under-fitting and Model Selection.ipynb		35- Model Evaluation part 2 Over-Under-fitting and Model Selection.ipynb
36- Model Evaluation part 3 Ridge Regression.ipynb		36- Model Evaluation part 3 Ridge Regression.ipynb
37- Model Evaluation part 4 Grid Search .ipynb		37- Model Evaluation part 4 Grid Search .ipynb
38- Assignment - Model Evaluation and Refinement.ipynb		38- Assignment - Model Evaluation and Refinement.ipynb
39- Data Visualization with Python.ipynb		39- Data Visualization with Python.ipynb
4- Number Methods.ipynb		4- Number Methods.ipynb
40- Line Plot .ipynb		40- Line Plot .ipynb
41- Area Plot.ipynb		41- Area Plot.ipynb
42- Histogram Plot.ipynb		42- Histogram Plot.ipynb
43- Bar Chart .ipynb		43- Bar Chart .ipynb
44- Exercise - Area Plots Histograms and Bar Plots - With Dataset.ipynb		44- Exercise - Area Plots Histograms and Bar Plots - With Dataset.ipynb
45- Pie Chart.ipynb		45- Pie Chart.ipynb
46- Box Plot.ipynb		46- Box Plot.ipynb
47- Scatter Plots.ipynb		47- Scatter Plots.ipynb
48- Exercise - Pie-Charts Box-Plots Scatter-Plots and Bubble-Plots.ipynb		48- Exercise - Pie-Charts Box-Plots Scatter-Plots and Bubble-Plots.ipynb
49- Waffle Charts.ipynb		49- Waffle Charts.ipynb
5- List, Dictionary, Sets, Tuples and Boolean .ipynb		5- List, Dictionary, Sets, Tuples and Boolean .ipynb
50- Word Clouds.ipynb		50- Word Clouds.ipynb
51- Exercise- Waffle-Charts Word-Clouds and Regression-Plots.jupyterlite.ipynb		51- Exercise- Waffle-Charts Word-Clouds and Regression-Plots.jupyterlite.ipynb
52- Regression Plots.ipynb		52- Regression Plots.ipynb
53- Folium Library.ipynb		53- Folium Library.ipynb
54- Exercise Folium - Generating Maps in Python.ipynb		54- Exercise Folium - Generating Maps in Python.ipynb
55- Heatmap.ipynb		55- Heatmap.ipynb
56- Plotly Library.ipynb		56- Plotly Library.ipynb
57- Exercise - Plotly Basics.ipynb		57- Exercise - Plotly Basics.ipynb
58- Exercise - Plotly Basics part 2.ipynb		58- Exercise - Plotly Basics part 2.ipynb
59_dash_basics_part_1.py		59_dash_basics_part_1.py
6- Numpy Arrays.ipynb		6- Numpy Arrays.ipynb
60_dash_population_visualizer_part_2.py		60_dash_population_visualizer_part_2.py
61_dash_chart_visualizer_part_3.py		61_dash_chart_visualizer_part_3.py
62_dash_flight_delay_part_4.py		62_dash_flight_delay_part_4.py
63_Dash_Practice_Assignment_1.py		63_Dash_Practice_Assignment_1.py
64_Practice_Assignment_2.py		64_Practice_Assignment_2.py
65_Graded_Final_Assignment.py		65_Graded_Final_Assignment.py
7- pandas - part 1.ipynb		7- pandas - part 1.ipynb
8- Pandas - Part 2.ipynb		8- Pandas - Part 2.ipynb
9- Pandas - part 3.ipynb		9- Pandas - part 3.ipynb
README.md		README.md

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