StephenFordham

@app.route('/login', methods=['POST', 'GET'])
def login():

    form = LoginForm()
    if form.validate_on_submit():
        user = User.query.filter_by(email=form.email.data).first()
        if user is None:
            flash('Please register to gain access', category='danger')
            return redirect(url_for('register'))

StephenFordham

fig = px.bar(plot_df, x='Provider County', y="Observed Prescribing Rate per 100 Visits", color="Provider County",
  animation_frame="Year", animation_group="Provider County", range_y=[3, 70], 
             title='Antibiotic Prescribing rates in US counties')
fig.show()

StephenFordham

keys = [i for i in range(65)]

all_dataframes = {}
for i, county in zip(keys, df['Provider County'].unique()):
    df2 = df[df['Provider County'] == county].sort_values('Year', ascending=True)
    all_dataframes[i] = df2 
    
master_df = []
for i in all_dataframes:
    master_df.append(all_dataframes[i])

StephenFordham

import pandas as pd 
import plotly.express as px
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
df = pd.read_csv('potentially-avoidable-antibiotic-prescribing-rates.csv')

StephenFordham

fig, ax = plt.subplots(figsize=(14, 16))

res_geo.plot(ax=ax, figsize=(14, 16), column=res_geo['resistance_scores'], cmap='cool', k=6,
            missing_kwds=dict(color="lightgrey",label='No Data/<10 isolates'),
            scheme='FisherJenks',
            edgecolor = 'black',
            legend=True, 
            linewidth = 0.1,
            legend_kwds=dict(loc='lower left', frameon=False, title='Resistance Scores'))

StephenFordham

res_geo.plot(figsize=(12, 16), column=res_geo['resistance_scores'], cmap='OrRd',
             edgecolor = 'black',
             linewidth = 0.1)

StephenFordham

data = gdf[gdf['country'].isin(res['country'].to_list())]
res_df = res.merge(data, on='country')
others = gdf[~gdf['country'].isin(res['country'].to_list())]
others['resistance_scores'] = np.NaN
res_geo = pd.concat([res_df, others])

StephenFordham

data_countries = res['country'].to_list()
all_countries = gdf['country'].to_list() 

same_countries = []
different_countries = []


for country in data_countries:
    if country not in all_countries:
        different_countries.append(country)

StephenFordham

res = pd.DataFrame(res.groupby('country').mean()['resistance_scores'].sort_values(ascending=False))
res = res[res.index.isin(representative_countires)].reset_index()

StephenFordham

res = pd.read_csv('resistance_score__Country__res_0-3_vir_0-5.csv')
res['resistance_scores'] = res['annotation'].apply(lambda x: int(x[0]))
res.drop('annotation', axis=1, inplace=True)
res.columns = ['country', 'resistance_scores']
res.groupby('country').mean()['resistance_scores'].sort_values(ascending=False)