MatPlotLib¶

Replicate Python Data Science Handbook Scatter Plot https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb with plotnine/ggplot

In [1]:

from sklearn.datasets import load_iris
iris = load_iris()
features = iris.data.T

In [2]:

import matplotlib.pyplot as plt

In [3]:

plt.scatter(features[0], features[1], alpha=0.2,
            s=100*features[3], c=iris.target, cmap='viridis')
plt.xlabel(iris.feature_names[0])
plt.ylabel(iris.feature_names[1]);

In [ ]:

Plot9 GGPLOT¶

In [4]:

import plotnine as p9
from plotnine import *
import pandas as pd
p9.options.figure_size = (5, 3.5)

In [5]:

from sklearn.datasets import load_iris
df = pd.DataFrame(load_iris(as_frame=True).data) # create a df from Bunch

In [6]:

## ggplot pipeline
( 
    ggplot( df, aes(df.columns[0], df.columns[1], color = df.columns[2], size = df.columns[3]))
    + geom_point()
)

Out[6]:

<ggplot: (129433389469)>