def pprint(arr, columns=('<STR_LIT>', '<STR_LIT>'),<EOL>names=('<STR_LIT>', '<STR_LIT>'),<EOL>max_rows=<NUM_LIT:32>, precision=<NUM_LIT:2>):
if max_rows is True:<EOL><INDENT>pd.set_option('<STR_LIT>', <NUM_LIT:1000>)<EOL><DEDENT>elif type(max_rows) is int:<EOL><INDENT>pd.set_option('<STR_LIT>', max_rows)<EOL><DEDENT>pd.set_option('<STR_LIT>', precision)<EOL>df = pd.DataFrame(arr.flatten(), index=arr['<STR_LIT:id>'].flatten(),<EOL>columns=columns)<EOL>df.columns = names<EOL>return df.style.format({names[<NUM_LIT:0>]: '<STR_LIT>',<EOL>names[<NUM_LIT:1>]: '<STR_LIT>'})<EOL>
Create a pandas DataFrame from a numpy ndarray.

By default use temp and lum with max rows of 32 and precision of 2.

arr - An numpy.ndarray.
columns - The columns to include in the pandas DataFrame. Defaults to
          temperature and luminosity.
names - The column names for the pandas DataFrame. Defaults to
        Temperature and Luminosity.
max_rows - If max_rows is an integer then set the pandas
           display.max_rows option to that value. If max_rows
           is True then set display.max_rows option  to 1000.
precision - An integer to set the pandas precision option.