For Tahmid Vai's work

geoplot.py

ncols = 3
nrows = 4

# create a figure of dimension nrows X ncols
fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 15))

# keeps track of the indexes of iaq
df_idx_counter = 0

# iterate through the grid and plot one iaq element in each grid box
for row_idx in range(nrows):
  for col_idx in range(ncols):
    # since manually incrementing, the index can get out of bound
    if df_idx_counter > len(iaq) - 1:
      break

    # query is based on date
    date = iaq.iloc[df_idx_counter]

    # increment index counter
    df_idx_counter += 1

    # get the dataframe to plot
    df_to_plot = gcdf_cs_1[gcdf_cs_1['aq_date'] == date]

    # axis is the box in the grid to plot the dataframe in
    axis = ax[row_idx][col_idx]

    # plot
    df_to_plot.plot(column='zone_id', cmap='summer', ax=axis, legend=True)
    axis.set_title('Analysis :'+ str(date))
plt.show()