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VERIFIED Sean Cody - Stu Collection - [1080p]Sean Cody - Stu Collection - [1080p]





Sean Cody - Stu Collection - [1080p]Sean Cody - Stu Collection - [1080p]









Sean Cody - Stu Collection - [1080p]Sean Cody - Stu Collection - [1080p]


Sean Cody - Stu Collection - [1080p] 2days9hours sean-cody-corjeny . I am thinking about using the following Python code: import pandas as pd df = pd.read_csv('2015-unique-company-name.csv') df1 = pd.DataFrame(columns=['common_name_as_filed', 'year']) for index, row in df.iterrows(): headers = list(row) common_name = ', '.join([i.lower() for i in headers]) df1 = df1.append(pd.DataFrame([common_name, headers, row], columns=['common_name_as_filed', 'year', 'company']) But I am not sure that the results I will get in the dataframe are what I want: I need to convert the company name to lower case and remove all the punctuation marks from the company name except for the '.' As an example of the results I get right now: common_name_as_filed year company Sean Cody - 2015 Sean Cody – I need to get: common_name_as_filed year company sean-cody 2015 Sean Cody The dataframe is not aligned with the headers for columns. I need to get the result in a dataframe that the headers can be aligned with the headers of the dataframe. I am wondering if there is any way to do this. I would be very grateful if you could guide me on the fastest way to achieve my result. A: Use dtype='object' with read_csv and pass a dict for the quoting argument, using the same setting for all columns in the same way as the following code shows: import pandas as pd df = pd.read_csv('./data.csv









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VERIFIED Sean Cody - Stu Collection - [1080p]Sean Cody - Stu Collection - [1080p]

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