Topics and Documents

So far, the following topics are included in this repository:

  • image processing

  • data visualization


Image Processing

The document picture_format.ipynb illustrates the following procedures:

  • how to generate images with numpy arrays

  • how to save them in .png format

  • how to load and convert them to Python lists

  • how to save them in .csv files

  • how to read them as pandas dataframes

Here an example of images generated in this document (digits in this case):

_images/digits.png

Here an example of the data content of these images in table format (px stands for pixel):

_images/data_table.png

The code documentation in this document is in German.


Data Visualization

The document basic_data_visualization_math.ipynb illustrates the following procedures:

  • how to generate data using mathematical functions

  • how to plot this data using matplotlib

  • how to change default plotting options and obtain customized plotting results

Here an example of plotted mathematical functions:

_images/function.png

The document basic_data_visualization_iris.ipynb is meant to visualize multidimensional data. Here, the classical Iris data set is used. This document illustrates the following procedures:

  • how to generate a pandas dataframe with data downloaded from a repository

  • how to generate different types of plots such as scatter plots, histograms, KDE-plots or boxplots

  • how to use alternative libraries (e.g. seaborn, numpy or scipy) and alternative methods for data visualization tasks

Here some examples:

Scatterplot

_images/iris_scatterplot.png

Boxplot

_images/iris_boxplot.png

Pairplot

_images/iris_pairplot.png

The code documentation in this document is in English.