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Reference Sheet

Day 1

Lesson02_HelloWorld_Variables

  • Use built-in Python functions (print).
  • Use mathematical operators to perform calculations (+ - * /).
  • Assign values to variables.
  • Use variables in mathematical equations.

Lesson03_Variables_Types

  • The type function.
  • The basic Python data types: int, float, string, and bool.
  • How to convert between different data types.

Lesson04_Lists_Intro

  • Make a list ([]).
  • Find the length of a list (len).
  • Add lists together (+).
  • Add things to a list (.append).

Lesson05_Indexing

  • Get an element from a list or string.
  • Get multiple elements from a list or string.

Lesson06_2D_Lists

  • How to make 2D lists.

Lesson07_2D_Lists_Indexing

  • How to index 2D lists.

Day 2

Lesson08_Functions_and_Methods

  • What functions and methods do.
  • The difference between functions and methods.
  • How to learn more about a certain function or method (using the help function).
  • New functions: max, min, sum, abs, round.
  • Functions can take arguments that modify the output.

Lesson09_Packages

  • How to import new functions in packages in Python, such as numpy.
  • More functions and methods:
    • mean (in numpy)
    • abs (in numpy)
    • sort

Lesson10_Pandas-Intro

  • How to import the pandas package with the nickname pd.
  • How to use DataFrames.
  • How to see the beginning & end of a DataFrame with the functions head & tail.

Lesson11_Pandas-Reading

  • How to read datasets from files into pandas DataFrames.
  • The index and columns attributes of DataFrames.
  • How to find the number of rows, columns, and number of data points in a DataFrame.

Lesson12_Pandas-Subsetting

  • How to use square brackets to subset columns.
  • How to use iloc to subset rows.
  • How to use iloc and square brackets at the same time.
  • How to use query to find rows where the column has a certain value.

Day 3

Lesson13_Numpy_Intro

  • Create an array with numpy.
  • Perform math with numpy arrays.

Lesson14_Basic_Stats_I

  • Calculate the mean of a set of values manually.
  • Use functions in numpy to calculate both the mean and median.

Lesson15_Basic_Stats_II

  • Calculate count statistics using collections.Counter.
  • Calculate percentages from count statistics.

Lesson16_Basics_Stats_III

  • Perform a t-test on a two-class dataset using ttest_ind from scipy.stats.
  • Interpret the results (pvalue) from a t-test.
  • Compute correlations for multiple variables using corrcoef from scipy.stats.

Day 4

Lesson17B_LineGraphs

  • Use the seaborn package with the nickname sns.
  • Load built-in datasets from seaborn with the load_dataset function.
  • Create a line plot with the lineplot function from seaborn.
  • Change the hue and style of lines based on categorical variables.

Lesson18B_Scatterplots

  • Create a scatter plot with the scatterplot function from seaborn.
  • Create a scatter plot with a line-of-best-fit with the lmplot function from seaborn.
  • Change the hue, style, and palette of a plot.

Lesson19B_BarCharts_Histograms

  • Create a bar plot with the barplot function from seaborn.
  • Remove missing values from data frames with the dropna function.
  • Create a histogram for continuous variables with the distplot function from seaborn.
  • Create a count plot for categorical variables with the countplot function from seaborn.