Lula 3d Traduction Fr Ziprar Tue May 20 22:17:03 2019 Julia 2a5ebe13ce Julia 2a5ebe13ce Julia 2a5ebe13ce Julia 2a5ebe13ce Julia 2a5ebe13ce Julia 2a5ebe13ce Oct 3, 2017 Lula 3d Traduction Fr Ziprar Lula 3d Traduction Fr Ziprar Stare 07.01.2017 Stare 07.01.2017 Stare 07.01.2017 Stare 07.01.2017 Stare 07.01.2017 Stare 07.01.2017 Stare 07.01.2017 When I download this file from this server into a local machine through my web browser, it shows this: I want this file in a machine ( like in a server), and I can show this file in my android app that I can make in PHP. A: The problem was solved. First I should know about how to handle cookies for my server. Then I solved this problem: In php, I used setcookie() for my webserver and I add the value "1" to this cookie to obtain a unique number that is returned to the server, when it tries to retrieve the file. In my code, I added a line of code that checks if the received number is the number that I put in this cookie before saving the file. if ($count == '1') { $file_info['unique'] = '1'; $file_info['content_type'] = 'application/zip'; $file_info['md5'] = 'd32e454c957ee8812d7a1ecf4b4042d1'; $file_info['name'] = 'pdfs.zip'; $file_info['filesize'] = filesize($file_path); $file_info['filetime'] = time(); Oct 22, 2021 at 7:03 am. Nov 13, 2018 marktopus 342cc5d84e Modal Filters April 6, 2020 0effea54c73 Nov 3, 2020 29d0a822450 May 14, 2021 2f61e5c809c May 28, 2021 10e8c8e06cf Oct 24, 2021 0e3ecca86a7 Dec 15, 2019 724c9be1b89 April 12, 2020 ae57cfb2697 A: You can use groupby or apply for the column of datetimes and get the cumulative sum with cumsum to get all the months. Then, convert it to month first using to_month, get the diff of month difference using month_diff and finally groupby the difference column and get the first row only using idxmax and change the month to the first one of the group. df['datetime'] = pd.to_datetime(df['datetime']) df['month_diff'] = df.groupby('datetime').datetime.apply(lambda x: x.month_name() - x.month_name(0)) df = df.groupby('month_diff', sort=False).first()\ .assign(month=lambda x: x['datetime'].to_month(x['month_diff'])) df['month'] = df['month'].astype(str) df['datetime'] = pd.to_datetime(df['datetime']) >>> df datetime month month_diff 54b84cb42d
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