code: def remove_nan(df, cols):
      """Remove rows with NaN values in specified column.
  
      Args:
          df (pandas.DataFrame): Pandas dataframe.
          cols (list of str): Name of columns in which to look for NaN.
  
      Returns:
          df (pandas.DataFrame): Pandas dataframe with invalid rows dropped.
  
      """
      for col in cols:
          # Convert any empty string cells to nan
          df[col].replace("", np.nan, inplace=True)
  
          # Remove NaN rows
          df = df[df[col].notna()]
  
      return df
  
file_path: recommenders/recommenders/datasets/covid_utils.py
imports: import numpy
  import pandas
  import requests
label_desc: Use image node_id 3 for calling a global function with example usage: remove_nan(df, cols) and returns: df