text_plain_output_1.png
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

df = pd.read_csv('/kaggle/input/yulu-bike-sharing-data/yulu_bike_sharing_dataset.csv')

df.shape

Q1 = df['count'].quantile(0.25)
Q3 = df['count'].quantile(0.75)

IQR = Q3 - Q1
upper_fence = Q3 + 1.5 * IQR
lower_fence = Q1 - 1.5 * IQR

df = df[(df['count'] > lower_fence) & (df['count'] < upper_fence)]

df.shape

round(df.corr(), 2)

sns.heatmap(df.corr(), linewidths=0.5)