Data Science with Python

Description

1. Dictionary and advanced Numpy (conditonal statements and loop)
1. Manipulating in Pandas
1. Joining Data with Python and SQL
1. Matplotlib
1. Seaborn
1. Cleaning data with python
1. Date and time in Python
1. Record Linkage
1. Write functions with Python
1. Toolbox in Python: Write functions, Lambda, List comprehension and generators
1. Exploratory data analysis in Python
1. Analyzing police activity with Pandas
1. Introduction to Statistics in Python
1. Introduction to Regression with statsmodels in Python(ols & SLR)
1. Sampling in Python
1. Hypothesis testing in Python
1. Supervised learning with scikit-learning
1. Unsupervised learning in Python
1. Machine learning with Tree-based models in Python

Name		Name	Last commit message	Last commit date
1.1 Dictionary and advanced Numpy.ipynb		1.1 Dictionary and advanced Numpy.ipynb
1.2 Manipulating in Pandas.ipynb		1.2 Manipulating in Pandas.ipynb
1.3 Joining data with Pandas and SQL.ipynb		1.3 Joining data with Pandas and SQL.ipynb
1.4 Matplotlib.ipynb		1.4 Matplotlib.ipynb
1.5 Seaborn.ipynb		1.5 Seaborn.ipynb
1.6 Cleaning_data.ipynb		1.6 Cleaning_data.ipynb
1.7 Working with Dates and Times.ipynb		1.7 Working with Dates and Times.ipynb
1.8 Record linkage.ipynb		1.8 Record linkage.ipynb
1.9 Write functions in Python.ipynb		1.9 Write functions in Python.ipynb
2.0 Toolbox for Python.ipynb		2.0 Toolbox for Python.ipynb
2.1 Exploratory Data Analysis in Python.ipynb		2.1 Exploratory Data Analysis in Python.ipynb
2.2 Analyzing Police Activity with pandas.ipynb		2.2 Analyzing Police Activity with pandas.ipynb
2.3 Introduction to statistics in python.ipynb		2.3 Introduction to statistics in python.ipynb
2.4 Introduction to Regression with statsmodels in Python.ipynb		2.4 Introduction to Regression with statsmodels in Python.ipynb
2.5 Sampling in Python.ipynb		2.5 Sampling in Python.ipynb
2.6 Hypothesis Testing in Python.ipynb		2.6 Hypothesis Testing in Python.ipynb
2.7 Supervised Learning with scikit-learn.ipynb		2.7 Supervised Learning with scikit-learn.ipynb
2.8 Unsupervised Learning in Python.ipynb		2.8 Unsupervised Learning in Python.ipynb
2.9 Machine Learning with Tree-Based Models in Python.ipynb		2.9 Machine Learning with Tree-Based Models in Python.ipynb
README.md		README.md