English | Size: 1.93 GB
Genre: eLearning
In this tutorial I teach pandas essentials. Pandas is a python library dedicated for data analysis. Is one of the most important tools of the modern machine learning developers. In the tutorial we cover all the functionality needed to head-start the data-analysis in pandas.
For the whole course we prepared detailed examples documented and executed in the jupyter lab notebooks. You can find source code on the course github. We highly recommend first to try to code the examples along the lecture. Use the source code as a last resource to overcome the errors. This way you will learn much more with the course :).
During the lessons we present example code run on the kaggle dataset which you can find on this link. To download the dataset from the kaggle you need to be registered. Registration is free. Kaggle is an ideal place for datasets dedicated for learning the machine learning :).
The agenda of the course is following:
Reading the dataframe and accessing attributes
Selecting from the dataframe
Indexing the dataframe
Column multi index
Updating the datframe
Joining the dataframes
Describing the dataframe (intro to exploratory analysis)
Iterating the dataframe
Group by
String, dates and sort
Basics of plotting
Writing the dataframe
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