code: def test_check_second_level_input_dataframe():
      with pytest.raises(
          ValueError,
          match="second_level_input DataFrame must have columns "
          "subject_label, map_name and effects_map_path",
      ):
          _check_second_level_input(
              pd.DataFrame(columns=["foo", "bar"]), pd.DataFrame()
          )
  
      with pytest.raises(
          ValueError,
          match="subject_label column must contain only strings",
      ):
          _check_second_level_input(
              pd.DataFrame(
                  {
                      "subject_label": [1, 2],
                      "map_name": ["a", "b"],
                      "effects_map_path": ["c", "d"],
                  }
              ),
              pd.DataFrame(),
          )
  
imports: import os
  from pathlib import Path
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image, load
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy import stats
  from nilearn._utils import testing
  from nilearn._utils.data_gen import generate_fake_fmri_data_and_design, write_fake_bold_img, write_fake_fmri_data_and_design
  from nilearn.glm.first_level import FirstLevelModel, run_glm
  from nilearn.glm.second_level import SecondLevelModel, non_parametric_inference
  from nilearn.glm.second_level.second_level import _check_confounds, _check_design_matrix, _check_effect_maps, _check_first_level_contrast, _check_input_as_first_level_model, _check_output_type, _check_second_level_input, _infer_effect_maps, _process_second_level_input_as_dataframe, _process_second_level_input_as_firstlevelmodels, _sort_input_dataframe
  from nilearn.image import concat_imgs, get_data, new_img_like, smooth_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 12 for calling a global function with example usage: test_check_second_level_input_dataframe() without return types