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Stub 1 (Python Libraries)

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    1980

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    PYTHON Session: NOT STARTED

     

    To compare multiple attributes with one another, use a scatterplot matrix.

    %matplotlib inline
import seaborn as sns

sns.set(style="ticks")

df = sns.load_dataset("iris")
sns.pairplot(df, hue="species")
    <seaborn.axisgrid.PairGrid at 0x7f97d574af28>
    import seaborn as sns
sns.set(style="ticks", palette="pastel")

# Load the example tips dataset
tips = sns.load_dataset("iris")

# Draw a nested boxplot to show bills by day and time
sns.boxplot(x="species", y="sepal_length", palette=["m", "g"],
            data=tips)
sns.despine(offset=10, trim=True)
    Image

     

    Or, you can create a heatmap.

    %matplotlib inline
from string import ascii_letters
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

sns.set(style="white")

# Generate a large random dataset
rs = np.random.RandomState(33)
d = pd.DataFrame(data=rs.normal(size=(100, 26)),
                 columns=list(ascii_letters[26:]))

# Compute the correlation matrix
corr = d.corr()

# Generate a mask for the upper triangle
mask = np.triu(np.ones_like(corr, dtype=np.bool))

# Set up the matplotlib figure
f, ax = plt.subplots(figsize=(11, 9))

# Generate a custom diverging colormap
cmap = sns.diverging_palette(220, 10, as_cmap=True)

# Draw the heatmap with the mask and correct aspect ratio
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,
            square=True, linewidths=.5, cbar_kws={"shrink": .5})
    <matplotlib.axes._subplots.AxesSubplot at 0x7f9167159a58>