Data distributions
Feature Engineering for Machine Learning in Python
Robert O'Callaghan
Director of Data Science, Ordergroove
Distribution assumptions
Observing your data
import matplotlib as plt
df.hist()
plt.show()
Delving deeper with box plots
Box plots in pandas
df[['column_1']].boxplot()
plt.show()
Paring distributions
import seaborn as sns
sns.pairplot(df)
Further details on your distributions
df.describe()
