There are two common ways to read the csv files.

pd.read_csv() is convenient since it directly change the file into a dataframe, but it cannot deal with the situaltion that the rows have different columns. In such situation, you can change to use csv and read the file line by line, in order to get the whole content.

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pandas.read_csv(filepath, delimiter=None, names=None)

We usually use read_csv() to read a csv file and turn it into dataframe. It is a very useful function. Sometimes we face the problem that the file has not a header and the first line will be the column names of the dataframe. To solve this problem, you can add your expected column names to "names" in the form of names = \['a', 'b', 'c'\]. 

Some times there are rows with exceptional column numbers. For example, 4 are needed but this row have 5. Thus, some error will stop the program. To solve this, you can set \[error_bad_lines = False\] to drop those lines.

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