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Views: 2116
Image: ubuntu2004
Kernel: Python 3 (system-wide)

Course structure

WeekWeek beginningLectureSelf-study NotebooksExercise NotebooksWorkshop NotebooksAssessment
121 Sept.PythonPython 1 to 4Python 3 and 4
228 Sept.Python 5 to 9Python 5 to 9Python Workshop 1
35 Oct.Python 10 to 14Python 10 to 14Python Workshop 2Python 1
412 Oct.Python 15 to 18Python 15 to 18Python Workshop 3Python 2
519 Oct.Python 19 to 23Python 19 to 23Python Workshop 4Python 3
626 Oct.EDAEDA 1 to 3EDA 1 to 3Python Workshop 5Python 4
72 Nov.EDA 4 to 7EDA 4 to 7EDA Workshop 1EDA 1
89 Nov.EDA 8 to 12EDA 9, 10 and 12EDA Workshop 2EDA 2
916 Nov.EDA Workshop 3EDA 3
1023 Nov.Data Analysis

EDA self-study and workshop Notebooks

1 - Exploring data with Python

  1. Displaying data

  2. Data analysis in Python

  3. Body mass of Alaskan sockeye salmon

  4. Reading a dataset from file

  5. Examining the dataset

2 - Plotting data - one numerical variable

  1. Plotting data

  2. One numerical variable: histograms

  3. Label your graphs

3 - One categorical variable

  1. Death by tiger

  2. Categories of the categorical variable

  3. Counting categories: Frequency table

    • Relative frequencies

  4. Rounding numbers in DataFrames

  5. Plotting frequencies: bar plot

  6. A principle of good table and graph design

  7. Never use pie charts!

EDA Workshop 1: Datasets of one variable

4 - Two numerical variables

  1. Guppy ornamentation

5 - Two categorical variables

  1. Avian malaria and reproduction

  2. Contingency table

  3. Displaying two categorical variables in a bar plot

6 - A categorical and one numerical variable

  1. Threespine sticklebacks

  2. Seaborn

  3. Stripplot

  4. Bar plot (a commonly used but poor graph)

  5. Boxplot

  6. Combine strip and boxplots

  7. How to interpret a boxplot

  8. Multiple histogram method

7 - A categorical and two numerical variables

  1. Kenyan finches

EDA Workshop 2: Datasets of two or more variables

8 - Describing data with summary statistics

  1. Summary statistics of categorical variables

  2. Summary statistics of numerical variables

9 - Describing location

  1. Walking in circles

  2. Mean or average

  3. Median

  4. Mode

  5. What do the "mean" and "median" mean?

10 - Describing variability or spread

  1. Range

  2. Inter quartile range

  3. Standard deviation

  4. All summary statistics

11 - Normal distribution and standard deviation

  1. What is the standard deviation?

    • The normal distribution

  2. Heights of college students

  3. The 68-95-99.7 rule

12 - Comparing statistics across categories

  1. Threespine sticklebacks

  2. Grouping data by category

EDA Workshop 3: Describing data