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Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if __name__ == "__main__": statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line. A very excellent Stack Overflow answer has more info on the if __name__ == "__main__": idiom in python.

Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if __name__ == "__main__": statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line. A very excellent Stack Overflow answer has more info on the if __name__ == "__main__": idiom in python.

Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if __name__ == "__main__": statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line. A very excellent Stack Overflow answer has more info on the if __name__ == "__main__": idiom in python.

Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if __name__ == "__main__": statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line. A very excellent Stack Overflow answer has more info on the if __name__ == "__main__": idiom in python.

Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if name == __main__: statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line.

Your functions don't return anything and don't take in any parameters. That means your modularization of the code is incomplete. The functions are relying on variables in the global namespace. Your main_dataset() function should probably take in either path or filenames as a parameter, for example, so that you don't have to modify your code to use it on different directories or files. That is, instead of def main_dataset():, you should write def main_dataset(path): for example. And it should probably end in return df. That way you don't have load df from the *.csv file again if you are going to use it in downstream analyses. frequency_table() should probably end in return freqDf (although note that freqDf is not a PEP8-recommend variable name).

If you chose, you could make the functions far more versatile by passing many more parameters. frequency_table() could take in a path (as a string) to be used for the output file, so it could save results anywhere. It could also take in neuter and non_neuter as parameters. (Those are good variable names BTW!)

Rather than having your two functions called explicitly at the bottom of the the code, the python idiom is to nest those calls under a if __name__ == "__main__": statement. That way the code is not run if you are just importing your file, but will be run if you call your file from the command line. A very excellent Stack Overflow answer has more info on the if __name__ == "__main__": idiom in python.