Question

给出一个 Pandas数据框，该数据框表示某些程序开始开始工作以及完成（即单行-单个程序）的时间：

      starts            finishes
2018-01-01 12:00    2018-01-01 15:00
2018-01-01 16:00    2018-01-01 20:00
2018-01-01 16:30    2018-01-01 20:00
2018-01-01 17:00    2018-01-01 21:00
                ...

我需要计算表中每次表示的并发程序数。上表如下：

      time             number_of_conc_progs
2018-01-01 12:00                 1
2018-01-01 15:00                 0
2018-01-01 16:00                 1
2018-01-01 16:30                 2               
2018-01-01 17:00                 3
2018-01-01 20:00                 1                
2018-01-01 21:00                 0 
                     ...

如果某个程序在12:00（例如）启动，并且当前进程数为 n ，则在12:00，该数字的值为 n +1 。

如果程序在12:00（例如）完成，并且当前进程数是 n ，则在12:00，该数字的值是 n -1 。

Answer 1

# creation of the dataframe
df = pd.DataFrame([
    ["2018-01-01 12:00", "2018-01-01 15:00"], 
    ["2018-01-01 16:00", "2018-01-01 20:00"], 
    ["2018-01-01 16:30", "2018-01-01 20:00"], 
    ["2018-01-01 17:00", "2018-01-01 21:00"]])
df.columns = ["starts", "finishes"]

# number of progs increases of 1 for start times
starts = pd.DataFrame()
starts["time"] = df.starts
starts["number_of_conc_progs"] = 1

# number of progs decreases of 1 for finishes times
finishes = pd.DataFrame()
finishes["time"] = df.finishes
finishes["number_of_conc_progs"] = -1

# then I merge the starts and the finishes dataframes
result = pd.DataFrame()
result = pd.concat([starts,finishes])
# I sort the time values
result = result.sort_values(by=['time'])
# If there is several starts or finishes at the same time, I sum them
result = result.groupby(['time']).sum()
# I do a cumulation sum to get the actual number of progs running
result.number_of_conc_progs = result.number_of_conc_progs.cumsum()

熊猫中的并发进程数

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