I am plotting some time series from .nc files using pandas, xarray and matplotlib. I have two datasets:

1. Sea Surface Temerature from 1982 to 2019, from which I plot the monthly mean for my area and represent the monthly temperature variation for those 37 years.
2. Sea Sea Surface Temerature from 2020 to 2021, where I plot the monthly variation for each of the years.

Two plot this, I use te following code (PLEASE NOTE THAT DUE TO MEMORY ALLOCATION ISSUES I HAD WHILE LOOPING THROUGH THE VARIABLES I WROTE A VERY BASIC CODE WITH NO LOOPS, SORRY FOR THAT!)

import xarray as xr
import matplotlib.pyplot as plt
from matplotlib import dates as md
import pandas as pd
import numpy as np
import netCDF4
import seaborn as sns
import marineHeatWaves as mhw
import datetime
sns.set()

ds_original = xr.open_dataset('sst_med_f81_to21_L4.nc')
ds_original_last = xr.open_dataset('sst_med_f20_to21_L4.nc')

extract_date = datetime.datetime.today()
date = extract_date.strftime("%Y-%m-%d")
ds1 = ds_original.sel(time=slice('1982-01-01','2019-12-31'))
ds2 = ds_original_last.sel(time=slice('2020-01-01','2020-12-31'))
ds3 = ds_original_last.sel(time=slice('2021-01-01', date))

# Convert to Pandas Dataframe
df1 = ds1.to_dataframe().reset_index().set_index('time')
df2 = ds2.to_dataframe().reset_index().set_index('time')
df3 = ds3.to_dataframe().reset_index().set_index('time')

#Converting to Celsius
def kelvin_to_celsius(temp_k):
    """
    Receives temperature in K and returns
    temperature in Cº
    """
    temp_c = temp_k - 273.15
    return temp_c

df1['analysed_sst_C'] = kelvin_to_celsius(df1['analysed_sst'])
df2['analysed_sst_C'] = kelvin_to_celsius(df2['analysed_sst'])
df3['analysed_sst_C'] = kelvin_to_celsius(df3['analysed_sst'])

#Indexing by month and yearday
df1['month'] = df1.index.month
df1['yearday'] = df1.index.dayofyear
df2['month'] = df2.index.month
df2['yearday'] = df2.index.dayofyear
df3['month'] = df3.index.month
df3['yearday'] = df3.index.dayofyear

# Calculating the average
daily_sst_82_19 = df1.analysed_sst_C.groupby(df1.yearday).agg(np.mean)
daily_sst_2020 = df2.analysed_sst_C.groupby(df2.yearday).agg(np.mean)
daily_sst_2021 = df3.analysed_sst_C.groupby(df3.yearday).agg(np.mean)

# Quick Plot
sns.set_theme(style="whitegrid")
fig, ax=plt.subplots(1, 1, figsize=(15, 7))
ax.xaxis.set_major_locator(md.MonthLocator())
ax.xaxis.set_major_formatter(md.DateFormatter('%b'))
ax.margins(x=0)
plt.plot(daily_sst_82_19, label='1982-2019')
plt.plot(daily_sst_2020,label='2020')
plt.plot(daily_sst_2021,label='2021', c = 'black')
plt.legend(loc = 'upper left')

I obtain the following plot:

I want my plot to start with Jan and end with Dec, but I cannot figure out where is the problem. I have tried to set x axis limit between to specific dates, but this creates a conflict as one of the time series is for 37 years and the other two are for 1 year only.

Any help would be very appreciated!!

UPDATE

I figured out how to move the months, specifying the follwing:

ax.xaxis.set_major_locator(MonthLocator(bymonthday=2))

So I obtained this:

But I still ned to delete that last Jan, and I cannot figure out how to do it.

CodePudding user response：

Okay so I figure out how to solve the issue.

Fine tunning plot parameters, I switched the DateFormatter to %D, to see the year as well. For my surprise, the year was set to 1970 and I have no idea why, because my oldest dataset starts in 1981. So once I discovered this, I set up the xlims to the ones you can read below and it worked pretty well:

#Add to plot settings:
ax.set_xlim(np.datetime64('1970-01-01'), np.datetime64('1970-12-31'))
ax.xaxis.set_major_locator(MonthLocator(bymonthday=1))
ax.xaxis.set_major_formatter(md.DateFormatter('%b'))

Result: