Python Introduction (Data Analytics)

Python Introduction (Data Analytics)

author

Luka

Category
Data 100 Level
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Course Description

Curriculums

Section 1 - Foundations of Numpy and Pandas

  • 0 Anaconda Installation
  • 1 Create Arrays
  • 2 Basic Operation of Arrays
  • 3 Indexing and Slicing
  • 4 Simple Array Operations
  • 5 Universal Functions
  • 6 Array Processing
  • 7 Save and Load Arrays
  • 8 Series
  • 9 DataFrame + Titanic Example
  • 10 Indexing Objects
  • 11 Reindex
  • 12 Drop Data
  • 13 Slice Data
  • 14 Data Alignment
  • 15 Rank and Sort

Section 2 - Data Manipulation

  • 1 Missing Value
  • 2 Merge
  • 3 Concatenate
  • 4 Combining DataFrames
  • 5 Stack and Unstack
  • 6 Duplicates in DataFrames
  • 7 Mapping
  • 8 Replace
  • 9 Rename index with map and rename
  • 10 Binning
  • 11 Outlier
  • 12 Permutation
  • 13 GroupBy on DataFrames (1)
  • 13 GroupBy on DataFrames (2)
  • 14 GroupBy on Dict and Series
  • 15 Aggregation

Section 3 - Data Visualization

  • 0 Matplotlib Introduction
  • 1 Simple Line Plot
  • 2 Subplot
  • 3 Scatter Plot
  • 4 Histogram
  • 5 Pie Plot
  • 6.1 Customizing Visualization – Twin Axes
  • 6.2 Customizing Visualization – add legend
  • 6.3 Customizing Visualization – colorbar
  • 6.4 Customizing Visualization – customize ticks
  • 7 Box Plot & Violin Plot
  • 8 Heatmap

Section 4 - Machine Learning

  • 0 Introduction to Machine Learning
  • 1.1 Linear Regression
  • 1.2 Linear Regression Demo
  • 2.1 Logistic Regression
  • 2.2 Logistic Regression Demo
  • 3.1 Multi-class Classification
  • 3.2 Multi-class Classification Demo
  • 4.1 Decision Tree
  • 4.2 Random Forest Tree
  • 4.3 Decision Tree & Random Forest Tree Demo

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