Style¶

[1]:

import seaborn as sns
import pandas as pd
import numpy as np
import gpplot

[2]:

gpplot.set_aesthetics()

Scatterplot¶

[3]:

nsamps = 20000
scatter_data = pd.DataFrame({'x': np.random.normal(size = nsamps)}, index = range(nsamps))
scatter_data['y'] = 2*scatter_data['x'] + np.random.normal(size = nsamps)
ax = gpplot.point_densityplot(scatter_data, 'x', 'y', palette=gpplot.sequential_cmap())

Boxplot¶

[4]:

tips = sns.load_dataset("tips")
ax = gpplot.dark_boxplot(data=tips, x="size", y="total_bill")

Heatmap¶

[5]:

flights = sns.load_dataset('flights')
flights['z-score'] = (flights.passengers - flights.passengers.mean())/flights.passengers.std()
spread_flights = flights.pivot("month", "year", "z-score")

[6]:

ax = sns.heatmap(spread_flights, cmap = gpplot.diverging_cmap(), center=0, square=True)