What data analysis isThe Python skills that you need for data analysisHow to use Jupyter Lab as your IDEHow to split the screen between two NotebooksHow to use Magic Commands Introduction to the Pandas Data FrameHow to examine the dataHow to access the columns and rowsHow to work with the dataHow to shape the dataHow to analyze the data Introduction to data visualizationHow to create 8 types of plotsHow to enhance a plot Introduction to SeabornHow to enhance and save plotsHow to create relational plotsHow to create categorical plotsHow to create distribution plotsOther techniques for enhancing a plot How to find the data that you want to analyzeHow to import data into a Data FrameHow to get database data into a Data FrameHow to work with a Stata fileHow to work with a JSON file Introduction to data cleaningHow to simplify the dataHow to find and fix missing valuesHow to fix data type problemsHow to find and to fix outliers How to add and modify columnsHow to apply functions and lambda expressionsHow to work with indexesHow to combine Data FramesHow to handle the Setting With Copy Warning How to create and plot long dataHow to group and aggregate the dataHow to create and use pivot tablesHow to work with binsMore skills for data analysis How to reindex time-series dataHow to resample time-series dataHow to work with rolling windowsHow to work with running totals Introduction to predictive analysisHow to find correlations between variablesHow to use Scikit-learn to work with a linear regressionHow to plot regression models with Seaborn A simple regression model for a Cars datasetHow to work with a multiple regression modelHow to work with categorical variablesHow to improve a multiple regression model