code: def test_eda_plot(iclaims_training_data):
      df = iclaims_training_data
      df["claims"] = np.log(df["claims"])
  
      # test plotting
      _ = eda_plot.ts_heatmap(
          df=df,
          date_col="week",
          value_col="claims",
          seasonal_interval=52,
          normalization=True,
      )
  
      var_list = ["trend.unemploy", "trend.filling", "trend.job"]
      _ = eda_plot.correlation_heatmap(df, var_list=var_list)
  
      _ = eda_plot.dual_axis_ts_plot(
          df=df, var1="trend.unemploy", var2="claims", date_col="week"
      )
  
      df[["week"] + var_list].melt(id_vars=["week"])
      _ = eda_plot.wrap_plot_ts(df, "week", ["week"] + var_list)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_eda_plot(iclaims_training_data) without return types