Question

我使用groupby生成了以下pd.DataFrame：

                       Timestemp  Altitude [m]  Sequence ID  Horizontal Wind Speed [m/s]  ...  Radial Wind Speed [m/s]  CNR [dB]  U-Component of Wind Speed  V-Component of Wind Speed 
0    2019-07-29 00:00:40.901           100       617375                       7.2750  ...                   -0.006   -15.706                   7.241811                  -0.694118
1    2019-07-29 00:00:40.901           150       617375                       8.0700  ...                    0.252   -14.960                   8.068156                  -0.172526
2    2019-07-29 00:00:40.901           200       617375                       9.6750  ...                    0.572   -13.872                   9.672698                  -0.211059
3    2019-07-29 00:00:40.901           250       617375                       9.7975  ...                    0.424   -12.584                   9.786624                   0.461525
4    2019-07-29 00:00:40.901           300       617375                       9.0325  ...                    0.054   -10.998                   9.029804                  -0.220684
...                      ...           ...          ...                          ...  ...                      ...       ...                        ...                        ...
1612 2019-07-29 00:16:59.713          1500       617425                          NaN  ...                      NaN       NaN                        NaN                        NaN
1613 2019-07-29 00:16:59.713          1550       617425                          NaN  ...                      NaN       NaN                        NaN                        NaN
1614 2019-07-29 00:16:59.713          1600       617425                          NaN  ...                      NaN       NaN                        NaN                        NaN
1615 2019-07-29 00:16:59.713          1650       617425                          NaN  ...                      NaN       NaN                        NaN                        NaN
1616 2019-07-29 00:16:59.713          1700       617425                          NaN  ...                      NaN       NaN                        NaN                        NaN

但是现在有点棘手了。我想计算每个单个高度上每5分钟的平均值和标准差。所以Timestemp与海拔高度超过5分钟。

我该如何解决？有人知道吗？谢谢

Answer 1

您可以使用resample将数据帧按5分钟的时间进行分组。首先，您需要将timestamp变量作为索引，然后应用resample函数。 “ T”代表分钟。您可以在这里找到所有代码列表：pandas resample documentation

df.set_index('Timestamp', inplace=True)
df.resample("5T").mean()
df.resample("5T").std()

编辑：如果您还想按“海拔”分组。请记住，您仍然需要在索引上加上时间戳。

df.groupby([pd.Grouper(freq="5Min"), "Altitude"]).mean()

df.groupby([pd.Grouper(freq="5Min"), "Altitude"]).std()

Answer 2

首先，您需要将时间列设置为索引。然后可以使用采样频率来计算平均值和标准偏差

df = df.set_index(pd.DatetimeIndex(df['Timestemp']))

dfmean = df.groupby(pd.Grouper(freq='5T')).mean()  # 5min
dfstd = df.groupby(pd.Grouper(freq='5T')).std()

有没有一种方法可以计算两个参数的标准差和均值？

2 个答案: