从数据集的给定日期范围中提取属于一天的数据 [英] Extracting data belonging to a day from a given range of dates on a dataset

问题描述

我有一个日期范围为2018年1月12日至8月3日的数据集，其中包含一些值:

I have a data set with a date range from January 12th to August 3rd of 2018 with some values:

my_df DataFrame的维数为:

The dimensionality of my_df DataFrame is:

my_df.shape 
(9752, 2)

每行包含半小时的班次

第一行始于2018-01-12

my_df.iloc[0]
Date:       2018-01-12 00:17:28
Value                      1
Name: 0, dtype: object

最后一行以2018-08-03

my_df.tail(1)
                  Date:     Value
9751    2018-08-03 23:44:59  1

我的目标是选择每天对应的数据行并将其导出到CSV文件.

My goal is to select the data rows corresponding to each day and export it to a CSV file.

要仅获取1月12日的数据并将其保存到可读文件中，请执行以下操作:

To get only the January 12th data and save to readable file, I perform:

# Selecting data value of each day
my_df_Jan12 = my_df[(my_df['Fecha:']>='2018-01-12 00:00:00') 
              & 
              (my_df['Fecha:']<='2018-01-12 23:59:59')
                                   ]
my_df_Jan12.to_csv('Data_Jan_12.csv', sep=',', header=True, index=False)

从1月12日到8月03日，共有203天(28周)

From January 12 to August 03 there are 203 days (28 weeks)

我不想每天手动执行此查询，因此我正在尝试以下基本分析:

I don't want to perform this query by each day manually, then I am trying the following basic analysis:

• 我需要生成203个文件(每天1个文件)
• 从1月12日(1月12日)开始的1月的一天
• 一月是第一个月(01)，八月是第八个月(08)

然后:

• 我需要遍历整个203天
  • ，并且必须在每个日期行中的值检查 起息日和日期，以检查更改 每个人
  • I need to iterate over the 203 days totality
    • and is necessary in each date row value check the month and day value date with the order to check the change of each one of them

    根据上述情况，我正在尝试这种方法:

    According to the above, I am trying this approach:

    # Selecting data value of each day (203 days)
    for i in range(203):
        for j in range(1,9): # month
            for k in range(12,32): # days of the month
                values = my_df[(my_df['Fecha:']>='2018-0{}-{} 00:00:00'.format(j,k)) 
                &  
                (my_df['Fecha:']<='2018-0{}-{} 23:59:59'.format(j,k))]
                values.to_csv('Values_day_{}.csv'.format(i), sep=',', header=True, index=False)
    

    但是我有一个问题，就是我在几个月的日子中迭代range(12,32)时，这个range(12,32)仅适用于一月的第一个月，我想是这样的...

    But I have the problem in the sense of when I iterate of range(12,32) in the days of the months, this range(12,32) only apply to first January month, I think so ...

    最后，由于我做错了某事，我得到了203个空CSV文件...

    Finally, I get 203 empty CSV files, due to something I am doing wrong ...

    如何以合适的方式应对这一小挑战? 任何方向都受到高度赞赏

    How to can I address this small challenge of the suited way? Any orientation is highly appreciated

    推荐答案

    是这样的吗?我将您的Date:原始列重命名为Timestamp.我还假设您拥有的Date:系列是熊猫DateTime系列.

    Something like this? I renamed your original column of Date: to Timestamp. I am also assuming that the Date: Series you have is a pandas DateTime series.

    my_df.columns = ['Timestamp', 'Value']
    my_df['Date'] = my_df['Timestamp'].apply(lambda x: x.date())
    dates = my_df['Date'].unique()
    for date in dates:
        f_name = str(date) + '.csv'
        my_df[my_df['Date'] == date].to_csv(f_name)
    

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