Normality of groups
Now that you've established equal variance, the next condition to check for is normality of the funding in each industry.
In this exercise, you'll visualize and compare data with and without normality. Although these visualizations can be created with plt.hist()
, for this exercise, you'll practice using the .plot()
argument on a DataFrame, with the arguments kind
and alpha
.
The three DataFrames you created (biotech_df
, enterprise_df
and ecommerce_df
) have been loaded for you. The packages pandas as pd
, NumPy as np
, Matplotlib as plt
, and the stats
package from SciPy have all been loaded as well.
Cet exercice fait partie du cours
Foundations of Inference in Python
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Plot a histogram of the funding for each industry
____.plot(kind=____, alpha=____)
____.plot(____)
____.plot(____)
plt.show()