plot histogram in seaborn
sns.distplot(gapminder['lifeExp'], kde=False, color='red', bins=100)
plt.title('Life Expectancy', fontsize=18)
plt.xlabel('Life Exp (years)', fontsize=16)
plt.ylabel('Frequency', fontsize=16)
plot histogram in seaborn
sns.distplot(gapminder['lifeExp'], kde=False, color='red', bins=100)
plt.title('Life Expectancy', fontsize=18)
plt.xlabel('Life Exp (years)', fontsize=16)
plt.ylabel('Frequency', fontsize=16)
multiple categories on distplot
import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
import seaborn as sns
iris = load_iris()
iris = pd.DataFrame(data=np.c_[iris['data'], iris['target']],
columns=iris['feature_names'] + ['target'])
# Sort the dataframe by target
target_0 = iris.loc[iris['target'] == 0]
target_1 = iris.loc[iris['target'] == 1]
target_2 = iris.loc[iris['target'] == 2]
sns.distplot(target_0[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_1[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_2[['sepal length (cm)']], hist=False, rug=True)
sns.plt.show()
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