Manage skewness
We've loaded the same dataset named data. Now your goal will be to remove skewness from var2 and var3 as they had a non-symmetric distribution as you've seen in the previous exercise plot. You will visualize them to make sure the problem is solved!
Libraries pandas, numpy, seaborn and matplotlib.pyplot have been loaded as pd, np, sns and plt respectively. Feel free to explore the dataset in the console.
Este exercício faz parte do curso
Customer Segmentation in Python
Instruções do exercício
- Apply a logarithmic transformation to
var2and store it as new variablevar2_log. - Apply a logarithmic transformation to
var3and store it as new variablevar3_log. - Plot the distribution of
var2_log. - Plot the distribution of
var3_log.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Apply log transformation to var2
data['____'] = np.____(data['____'])
# Apply log transformation to var3
data['____'] = ____.____(____)
# Create a subplot of the distribution of var2_log
plt.____(2, 1, 1); ____.____(data['____'])
# Create a subplot of the distribution of var3_log
plt.____(2, 1, 2); ____.____(data['____'])
# Show the plot
plt.show()