<jupyter_start><jupyter_text>Libraries<jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns

import plotly.graph_objects as go
import plotly.express as px
from plotly.subplots import make_subplots

import warnings
warnings.filterwarnings('ignore')<jupyter_output><empty_output><jupyter_text>Load data<jupyter_code>coronaTX = pd.read_csv("texas-history.csv")
coronaTX.head(20)
print(coronaTX.columns)<jupyter_output>Index(['date', 'state', 'dataQualityGrade', 'death', 'deathConfirmed',
       'deathIncrease', 'deathProbable', 'hospitalized',
       'hospitalizedCumulative', 'hospitalizedCurrently',
       'hospitalizedIncrease', 'inIcuCumulative', 'inIcuCurrently', 'negative',
       'negativeIncrease', 'negativeTestsAntibody',
       'negativeTestsPeopleAntibody', 'negativeTestsViral',
       'onVentilatorCumulative', 'onVentilatorCurrently', 'positive',
       'positiveCasesViral', 'positiveIncrease', 'positiveScore',
       'positiveTestsAntibody', 'positiveTestsAntigen',
       'positiveTestsPeopleAntibody', 'positiveTestsPeopleAntigen',
       'positiveTestsViral', 'recovered', 'totalTestEncountersViral',
       'totalTestEncountersViralIncrease', 'totalTestResults',
       'totalTestResultsIncrease', 'totalTestsAntibody', 'totalTestsAntigen',
       'totalTestsPeopleAntibody', 'totalTestsPeopleAntigen',
       'totalTestsPeopleViral', 'totalTestsPeopleViralIncrease',
       'totalTestsViral'[...]<jupyter_text>Visualization<jupyter_code>data = coronaTX[['date', 'death', 'hospitalizedCurrently', 'onVentilatorCurrently']]
area_data = pd.DataFrame(columns=['date', 'metric', 'cases'])
for i, r in data.iterrows():
    for m in ['death', 'hospitalizedCurrently', 'onVentilatorCurrently']:
        area_data = area_data.append(
            {'date': r['date'], 'Metric': m, 'Cases': r[m]},
            ignore_index=True)

    
fig = px.area(area_data, x="date", y="Cases", color="Metric",
	      line_group="Metric"
)
fig.show()<jupyter_output><empty_output>
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