Je data verkennen met visualisaties

Marketinganalyse: klantverloop voorspellen in Python

Mark Peterson

Director of Data Science, Infoblox

Data visualiseren in Python

import matplotlib.pyplot as plt
import seaborn as sns

sns.distplot(telco['Account_Length'])

plt.show()

verdeling accountlengte.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

Screenshot 2019-05-10 11.25.40.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

gekleurde boxen.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

25e percentiel.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

75e percentiel.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco)

plt.show()

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco,
            sym="")

plt.show()

Screenshot 2019-05-10 11.30.18.png

sns.boxplot(x = 'Churn',
            y = 'Account_Length',
            data = telco,
            hue = 'Intl_Plan')

plt.show()

Screenshot 2019-05-10 11.41.29.png

Marketinganalyse: klantverloop voorspellen in Python