Understanding your data

You will soon start building models in Keras to predict wages based on various professional and demographic factors. Before you start building a model, it's good to understand your data by performing some exploratory analysis.

The data is pre-loaded into a pandas DataFrame called df. Use the .head() and .describe() methods in the IPython Shell for a quick overview of the DataFrame.

The target variable you'll be predicting is wage_per_hour. Some of the predictor variables are binary indicators, where a value of 1 represents True, and 0 represents False.

Of the 9 predictor variables in the DataFrame, how many are binary indicators? The min and max values as shown by .describe() will be informative here. How many binary indicator predictors are there?

Exercise

Understanding your data

Instructions

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