熊猫将功能应用于列的第二行

Question

我试图在插值行之间的数值后每隔第二行更改文本。

    stamp     value
0   00:00:00  2
1   00:00:00  3
2   01:00:00  5

尝试将此更改应用于第二个图章行（即冒号之间为30而不是00）-str列

    stamp     value
0   00:00:00  2
1   00:30:00  3
2   01:00:00  5

更改字符串的功能

def time_vals(row):
    #run only on odd rows (1/2 hr)
    if int(row.name) % 2 != 0:
        l, m, r = row.split(':')
        return l+":30:"+r

我尝试了以下方法：

hh_weather['time'] =hh_weather[hh_weather.rows[::2]['time']].apply(time_vals(2))

但是出现错误：AttributeError：'DataFrame'对象没有属性'rows'

当我尝试时：

hh_weather['time'] = hh_weather['time'].apply(time_vals)

AttributeError：'str'对象没有属性'name'

有什么想法吗？

Answer 1

使用timedelta代替str

Pandas的优势在于矢量化功能。在这里，您可以使用timedelta用数字表示时间。如果数据如您的示例所示，即秒始终为零，那么您可以按小时进行累加并增加30分钟。然后有条件地将此系列分配给df['stamp']。

# convert to timedelta
df['stamp'] = pd.to_timedelta(df['stamp'])

# create series by flooring by hour, then adding 30 minutes
s = df['stamp'].dt.floor('h') + pd.Timedelta(minutes=30)

# assign new series conditional on index
df['stamp'] = np.where(df.index % 2, s, df['stamp'])

print(df)

     stamp  value
0 00:00:00      2
1 00:30:00      3
2 01:00:00      5

Answer 2

#convert string value to timedelta (better to work with time)
df['stamp']=pd.to_timedelta(df['stamp'])

#slicing only odd row's from `stamp` column and adding 30 minutes to all the odd row's
odd_df=pd.to_timedelta(df.loc[1::2,'stamp'])+pd.to_timedelta('30 min')

#updating new series (out_df) with the existing df, based on index.
df['stamp'].update(odd_df)

#print(df)
    stamp   value
0   00:00:00    2
1   00:30:00    3
2   01:00:00    5