Introduction
Python functions you should know
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Getting the most from this course
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1. Fundamental Built-In Python Functions for Data Science
Python print() function
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Python input() function
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Python abs() function
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Python round() function
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Python min() function
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Python max() function
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Python sorted() function
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Python sum() function
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Python len() function
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Python type() function
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2. Advanced Built-In Python Functions for Data Science
Python map() function
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Python zip() function
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Python filter() function
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3. Functions from NumPy Library for Manipulation of Numerical Data
Create NumPy arrays in Python
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Minimum and maximum values in NumPy arrays
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Indices of min and max values in NumPy arrays
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Find shapes of NumPy arrays and reshape
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Select items or groups of items from NumPy arrays
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Arithmetic operations on NumPy arrays
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Scalar operations on NumPy arrays
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Statistical operations on NumPy arrays
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Other operations on NumPy arrays
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4. Functions from SciPy Library for Scientific Computing
Linear algebra operations with SciPy
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Statistical functions with SciPy
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5. Functions from pandas Library for Data Manipulation and Data Analysis
Create a pandas series
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Create a pandas DataFrame
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Select data subsets from pandas objects
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Modify pandas objects
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Combine data from pandas objects
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Group data from pandas objects
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6. Functions from Matplotlib for Data Visualization
Matplotlib line plots
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Matplotlib scatter plots
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Matplotlib bar plots
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Matplotlib pie charts
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Matplotlib histograms
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Matplotlib subplots
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7. Functions from Seaborn for Data Visualization
Seaborn box plots
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Seaborn kernel density estimate plots
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Seaborn violin plots
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Seaborn heatmaps
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Conclusion
Get started using Python functions
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Ex_Files_Python_Data_Functions.zip
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