text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

df = pd.read_csv('../input/energy-consumption-generation-prices-and-weather/energy_dataset.csv')

round(df.isnull().sum() / len(df) * 100, 2)

df.corr()

correlations = df.corr(method='pearson')

plt.figure(figsize=(15, 12.5))
sns.heatmap(df.corr(), annot=True, cmap='Blues', linewidth=0.9)
plt.show()