air quality plots

airquality.py

# for every city, we fetch and plot data from all available parameters
import openaq
import matplotlib.pyplot as plt
import seaborn as sns

sns.set(style="white", palette='muted', font_scale=1.35, color_codes=True)
api = openaq.OpenAQ()
def get_city_data(city='Santiago'):
    df = api.measurements(city=city, limit=10000, df=True)
    df = df.query("value >= 0.0")  # clean up the data by removing values below 0
# Map the gas species from ugm3 to ppb (gas-phase species only)
    df['corrected'] = df.apply(lambda x: openaq.utils.mass_to_mix(x['value'], 
                                                              x['parameter'], unit='ppm'), axis=1)
    return df

  def dateplot(y, **kwargs):
    ax = plt.gca()
    data = kwargs.pop("data")
    rs = kwargs.pop("rs", '12h')
    data.resample(rs).mean().plot(y=y, ax=ax, grid=False, **kwargs)

df = get_city_data(')
g = sns.FacetGrid(df, col='parameter', col_wrap=3, size=4, hue='parameter', sharey=False)
g.map_dataframe(dateplot, "corrected", rs='12h')    # Map the dataframe to the grid
g.set_titles("{col_name}", fontsize=16)# Set the titles
g.set_axis_labels("", "value")         # Set the axis labels