code: def test_seasonal_plot(close_figures):
      rs = np.random.RandomState(1234)
      data = rs.randn(20, 12)
      data += 6 * np.sin(np.arange(12.0) / 11 * np.pi)[None, :]
      data = data.ravel()
      months = np.tile(np.arange(1, 13), (20, 1))
      months = months.ravel()
      df = pd.DataFrame([data, months], index=["data", "months"]).T
      grouped = df.groupby("months")["data"]
      labels = [
          "Jan",
          "Feb",
          "Mar",
          "Apr",
          "May",
          "Jun",
          "Jul",
          "Aug",
          "Sep",
          "Oct",
          "Nov",
          "Dec",
      ]
      fig = seasonal_plot(grouped, labels)
      ax = fig.get_axes()[0]
      output = [tl.get_text() for tl in ax.get_xticklabels()]
      assert_equal(labels, output)
  
imports: from statsmodels.compat.pandas import MONTH_END
  from statsmodels.compat.python import lmap
  import calendar
  from io import BytesIO
  import locale
  import numpy
  from numpy.testing import assert_, assert_equal
  import pandas
  import pytest
  from statsmodels.datasets import elnino, macrodata
  from statsmodels.graphics.tsaplots import month_plot, plot_accf_grid, plot_acf, plot_ccf, plot_pacf, plot_predict, quarter_plot, seasonal_plot
  from statsmodels.tsa import arima_process
  from statsmodels.tsa.ar_model import AutoReg
  from statsmodels.tsa.arima.model import ARIMA
label_desc: Use image node_id 12 for calling a global function with example usage: test_seasonal_plot(close_figures) without return types