<jupyter_start><jupyter_text><jupyter_code>import pandas as pd 
from google.colab import files
upload = files.upload()
dataset = pd.read_csv("weatherHistory.csv")
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
dataset.head()
dataset.isnull().sum()
dataset.info()
dataset['Formatted Date']= pd.to_datetime(dataset['Formatted Date'] , utc=True)
dataset['Formatted Date']
dataset = dataset.set_index('Formatted Date')
dataset.head()
data_columns = ['Apparent Temperature (C)','Humidity']
df_monthly_mean = dataset[data_columns].resample('MS').mean()
df_monthly_mean.head()
df_monthly_mean
df1 = df_monthly_mean[df_monthly_mean.index.month==4]
print(df1)

df1.dtypes
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")

plt.figure(figsize=(14,6))
plt.title("Variation in Apparent Temperature vs Humidity")
sns.lineplot(data=df_monthly_mean)
import matplotlib.dates as mdates
from datetime import datetime

fig, ax = plt.subplots(figsize=(15,5))
ax.plot(df1.loc['2006-04-01': '2016-04-01','Apparent Temperature (C)'], marker='o',linestyle='-',label='Apparent Temperature (C)')
ax.plot(df1.loc['2006-04-01': '2016-04-01','Humidity'], marker='o',linestyle='-', label='Humidity')
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
ax.legend(loc ='center right')
ax.set_xlabel('Month of April')<jupyter_output><empty_output>
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