text_plain_output_1.png
import io

import pandas as pd

import requests

import pandas as pd
data = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/breast-cancer-wisconsin.data', header=None)
data.columns = ['Sample code', 'Clump Thickness', 'Uniformity of Cell Size', 'Uniformity of Cell Shape', 'Marginal Adhesion', 'Single Epithelial Cell Size', 'Bare Nuclei', 'Bland Chromatin', 'Normal Nucleoli', 'Mitoses', 'Class']
data = data.drop(['Sample code'], axis=1)

#modified to load from remote URL, Ye 2021
import requests
import io
url = "https://cgi.luddy.indiana.edu/~yye/b565/data/DTW_prec.csv"
s=requests.get(url).content
daily = pd.read_csv(io.StringIO(s.decode('utf-8')), header='infer')
daily.index = pd.to_datetime(daily['DATE'])
daily = daily['PRCP']
ax = daily.plot(kind='line',figsize=(15,3))
ax.set_title('Daily Precipitation (variance = %.4f)' % (daily.var()))

monthly = daily.groupby(pd.Grouper(freq='M')).sum()
ax = monthly.plot(kind='line', figsize=(15, 3))
ax.set_title('Monthly Precipitation (variance = %.4f)' % monthly.var())