This Kernel is an index accompanying a series of tutorial notebooks introducing Python for data analysis. This series is intended for those new to data science, programming and Python. It is an updated version of a guide I previously posted on my blog.
I am also creating a 30-Part YouTube series covering each lesson in a video format. If you’re interested in that, view the Python for Data Analysis Playlist.
Index¶
Section 1: Getting Started¶
1: Getting Started
2: Python Arithmetic
3: Basic Data Types
Section 2: Data Structures¶
4: Variables
5: Lists
6: Tuples and Strings
7: Dictionaries and Sets
8: Numpy Arrays
9: Pandas DataFrames
10: Reading and Writing Data
Section 3: Programming Constructs¶
11: Control Flow
12: Functions
13: List Comprehensions
Section 4: Data Exploration and Cleaning¶
14: Data Exploration and Cleaning
15: Working With Text Data
16: Preparing Numeric Data
17: Dealing With Dates
18: Merging Data
19: Frequency Tables
20: Plotting with pandas
Section 5: Basic Statistics¶
21: Descriptive Statistics
22: Probability Distributions
23: Confidence Intervals
Section 6: Inferential Statistics¶
24: Hypothesis Testing
25: Chi-Squared Tests
26: ANOVA
Section 7: Predictive Modeling¶
27: Linear Regression
28: Logistic Regression
29: Decision Trees
30: Random Forests