用自第一行以来的分钟数更新每一行

Question

我有一个包含一百万条推文的文件。第一条推文发生在2013-04-15 20:17:18 UTC。我想用自minsSince 第一条推文以来的分钟数更新每条推文行。

我找到了有关日期时间 here 和转换时间 here 的帮助，但是当我将两者放在一起时，我没有得到正确的时间。它可能是每个 published_at 值末尾的 UTC 字符串。

它抛出的错误是：

tweets['minsSince'] = tweets.apply(timesince,axis=1)
...
TypeError: ('string indices must be integers, not str', u'occurred at index 0')

感谢您的帮助。

#Import stuff
from datetime import datetime
import time
import pandas as pd
from pandas import DataFrame

#Read the csv file
tweets = pd.read_csv('BostonTWEETS.csv')
tweets.head()

#The first tweet's published_at time
starttime = datetime (2013, 04, 15, 20, 17, 18)

#Run through the document and calculate the minutes since the first tweet
def timesince(row):
    minsSince = int()
    tweetTime = row['published_at']
    ts = time.strftime('%Y-%m-%d %H:%M:%S', time.strptime(tweetTime['published_at'], '%Y-%m-%d %H:%M:%S %UTC'))
    timediff = (tweetTime - starttime)
    minsSince.append("timediff")
    return ",".join(minsSince)

tweets['minsSince'] = tweets.apply(timesince,axis=1)

df = DataFrame(tweets)

print(df)

前 5 行的示例 csv file。

Answer 1

#Import stuff
from datetime import datetime
import time
import pandas as pd
from pandas import DataFrame

#Read the csv file
tweets = pd.read_csv('sample.csv')
tweets.head()

#The first tweet's published_at time
starttime = tweets.published_at.values[0]
starttime = datetime.strptime(starttime, '%Y-%m-%d %H:%M:%S UTC')

#Run through the document and calculate the minutes since the first tweet
def timesince(row):
    ts = datetime.strptime(row, '%Y-%m-%d %H:%M:%S UTC')
    timediff = (ts- starttime)
    timediff = divmod(timediff.days * 86400 + timediff.seconds, 60)
    return timediff[0]

tweets['minSince'] = 0
tweets.minSince = tweets.published_at.map(timesince)

df = DataFrame(tweets)

print(df)

我希望这是您正在寻找的。