問題描述
我有以下使用時(shí)間戳索引的數(shù)據(jù)幀結(jié)構(gòu):
I have the following dataframe structure that is indexed with a timestamp:
neg neu norm pol pos date
time
1520353341 0.000 1.000 0.0000 0.000000 0.000
1520353342 0.121 0.879 -0.2960 0.347851 0.000
1520353342 0.217 0.783 -0.6124 0.465833 0.000
我根據(jù)時(shí)間戳創(chuàng)建一個(gè)日期:
I create a date from the timestamp:
data_frame['date'] = [datetime.datetime.fromtimestamp(d) for d in data_frame.time]
結(jié)果:
neg neu norm pol pos date
time
1520353341 0.000 1.000 0.0000 0.000000 0.000 2018-03-06 10:22:21
1520353342 0.121 0.879 -0.2960 0.347851 0.000 2018-03-06 10:22:22
1520353342 0.217 0.783 -0.6124 0.465833 0.000 2018-03-06 10:22:22
我想按小時(shí)分組，同時(shí)獲得除時(shí)間戳以外的所有值的平均值，應(yīng)該是小時(shí)小組開始的地方.所以這是我要?dú)w檔的結(jié)果:
I want to group by hour, while getting the mean for all the values, except the timestamp, that should be the hour from where the group started. So this is the result I want to archive:
neg neu norm pol pos
time
1520352000 0.027989 0.893233 0.122535 0.221079 0.078779
1520355600 0.028861 0.899321 0.103698 0.209353 0.071811
到目前為止，我得到的最接近的是這個(gè) 回答:
The closest I have gotten so far has been with this answer:
data = data.groupby(data.date.dt.hour).mean()
結(jié)果:
neg neu norm pol pos
date
0 0.027989 0.893233 0.122535 0.221079 0.078779
1 0.028861 0.899321 0.103698 0.209353 0.071811
但我不知道如何保留考慮到 grouby 開始時(shí)間的時(shí)間戳.
But I cant figure out how to keep the timestamp that takes in account he hour where the grouby started.
推薦答案
我遇到了這個(gè) gem，pd.DataFrame.resample，在我發(fā)布了按小時(shí)計(jì)算的解決方案之后.
I came across this gem, pd.DataFrame.resample, after I posted my round-to-hour solution.
# Construct example dataframe
times = pd.date_range('1/1/2018', periods=5, freq='25min')
values = [4,8,3,4,1]
df = pd.DataFrame({'val':values}, index=times)
# Resample by hour and calculate medians
df.resample('H').median()
或者你可以使用 groupby 與 Grouper 如果您不想將時(shí)間作為索引:
Or you can use groupby with Grouper if you don't want times as index:
df = pd.DataFrame({'val':values, 'times':times})
df.groupby(pd.Grouper(level='times', freq='H')).median()
這篇關(guān)于如何使用帶有 Pandas 的時(shí)間戳按小時(shí)對(duì)數(shù)據(jù)幀進(jìn)行分組的文章就介紹到這了，希望我們推薦的答案對(duì)大家有所幫助，也希望大家多多支持html5模板網(wǎng)！