Plot seperate seasonal plots with datetime dataframe-CodePudding

I have a dataframe df:

    Date    station_name    BD_val      TEMIS_val   ratio       longitude   latitude
0   2003-01 29              295.448387  291.225806  -1.429211   158.950 -   54.500
1   2003-01 57              282.258065  279.290323  -1.051429   -26.130     -75.360
2   2003-01 57              282.258065  279.290323  -1.051429   -26.600     -75.583
3   2003-01 101             310.516129  304.677419  -1.880324   39.580      -69.010
4   2003-01 111             268.071429  274.000000  2.211564    -24.800     -89.983
... ... ... ... ... ... ... ...
153 2003-12 400             294.733333  300.000000  1.786926    11.450      -70.450
154 2003-12 454             298.176667  294.000000  -1.400736   -67.106     -68.130
155 2003-12 473             308.433333  316.000000  2.453258    -70.850     -53.140
156 2003-12 478             309.306667  304.000000  -1.715665   76.380      -69.370

Where Date is in datetime format.

I want to create 4 plots: one each for a three month period, starting from Jan-Mar where latitude is on the x-axis, and ratio is on the y-axis. I want each month then to be a single line in that specific subplot.

How would I go about doing this?

So far, I have used the following method:

for key, grp in comp_df_complete.groupby(['Date']):
    grp = grp.sort_values(by=['latitude'])
    plt.plot(grp.latitude, grp.ratio)

plt.legend()
plt.show()

Which results in the following plot:

Which is close, with the issues being it's cluttered, plus I want each month in the 4 seasons to be visible too, in 4 faceted plots. Furthermore, the legend doesn't seem to work with this method, but that's for another question:

No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.

What I finally would want is a figure similar to this one:

But with latitude on the x-axis, ratio on the y-axis and three lines per plot for each month in the specific season.

CodePudding user response：

Assuming that the values in Date are strings, the idea is to add a column giving the 'season' and for each, group by Date to get the lines for every month of a given season:

df['season'] = df['Date'].apply(lambda x: (int(x[-2:])-1)//3 1)
fig = plt.figure(figsize=(16, 12))

for i in range(4):  
    ax = fig.add_subplot(2, 2, i 1)
    for key, grp in df[df['season']==i 1].groupby(['Date']):
        grp = grp.sort_values(by=['latitude'])
        ax.plot(grp.latitude, grp.ratio)
plt.show()