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Multiple Box Plot using Seaborn

# Visualization is the easiest way to have an inference about the overall data and the outliers.
n = 1
plt.figure(figsize=(18,15))
for column in df.describe().columns:
  plt.subplot(5, 4, n)
  n = n+1
  sns.boxplot(df[column])
  plt.tight_layout()

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seaborn boxplot multiple for each column

import numpy as np; np.random.seed(42)
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame(data = np.random.random(size=(4,4)), columns = ['A','B','C','D'])

sns.boxplot(x="variable", y="value", data=pd.melt(df))

plt.show()

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Multiple Box Plot using Seaborn

seaborn boxplot multiple for each column

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