In [2]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

plt.rcParams['figure.figsize'] = (11, 8.5)


    

In [3]:

    

data = pd.read_csv('~/Dropbox/gw_data.csv')


    

In [4]:

    

upgradient = ['MW-1', 'MW-2', 'MW-4', 'MW-6']
downgradient = ['MW-3', 'MW-5', 'MW-7', 'MW-8']
data['gradient'] = np.where(data['location_id'].isin(upgradient), 'upgradient', 'downgradient')


    

In [5]:

    

params = ['Arsenic, dissolved', 'Boron, dissolved', 'Chloride, total']


    

In [6]:

    

data = data[(data['location_id'].isin(upgradient) | data['location_id'].isin(downgradient)) & data['param_name'].isin(params)]


    

In [7]:

    

from enviropy import plots


    

In [8]:

    

plots.boxplot(data, wells=(upgradient+downgradient), analytes=params)


    

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