我有一些组合代码的问题,我很确定曾经运行过(在较旧的pandas版本上).在0.9,我得到没有数字类型来聚合错误.有任何想法吗？
In [31]: data
Out[31]:
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 2557 entries, 2004-01-01 00:00:00 to 2010-12-31 00:00:00
Freq: <1 DateOffset>
Columns: 360 entries, -89.75 to 89.75
dtypes: object(360)
In [32]: latedges = linspace(-90., 90., 73)
In [33]: lats_new = linspace(-87.5, 87.5, 72)
In [34]: def _get_gridbox_label(x, bins, labels):
....: return labels[searchsorted(bins, x) - 1]
....:
In [35]: lat_bucket = lambda x: _get_gridbox_label(x, latedges, lats_new)
In [36]: data.T.groupby(lat_bucket).mean()
---------------------------------------------------------------------------
DataError Traceback (most recent call last)
<ipython-input-36-ed9c538ac526> in <module>()
----> 1 data.T.groupby(lat_bucket).mean() …我有三个数据帧:时间戳(带时间戳),dataSun(带有日出和日落的时间戳),dataData(带有不同的气候数据).Dataframe timestamp具有数据类型"int64".
timestamp.head()
timestamp
0 1521681600000
1 1521681900000
2 1521682200000
3 1521682500000
4 1521682800000
Dataframe dataSun也有数据类型"int64".
dataSun.head()
sunrise sunset
0 1521696105000 1521740761000
1 1521696105000 1521740761000
2 1521696105000 1521740761000
3 1521696105000 1521740761000
4 1521696105000 1521740761000
具有气候数据的数据框具有数据dataData类型"float64".
dataData.head()
temperature pressure humidity
0 2.490000 1018.000000 99.0
1 2.408333 1017.833333 99.0
2 2.326667 1017.666667 99.0
3 2.245000 1017.500000 99.0
4 2.163333 1017.333333 99.0
5 2.081667 1017.166667 99.0
我想将这三个数据帧连接在一起.
dataResult = pd.concat((timestamp, dataSun, dataData), axis …