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小弟使用pandas的统计函数mean求均值，但是结果是空值，请求论坛大神们帮小弟解惑啊！

小弟使用pandas的统计函数mean，求一下df各列的平均，但是结果是空值，请求论坛大神们帮小弟解惑啊，下面是打印的df和mean函数输出的均值结果。
df长这样：
VERSION MODEL FCST_LEAD FCST_VALID_BEG FCST_VALID_END OBS_LEAD \
5 V5.2 WRF 480000 20180507_000000 20180507_000000 0

5 V5.2 WRF 480000 20180508_000000 20180508_000000 0

5 V5.2 WRF 480000 20180509_000000 20180509_000000 0

5 V5.2 WRF 480000 20180510_000000 20180510_000000 0

5 V5.2 WRF 480000 20180511_000000 20180511_000000 0

5 V5.2 WRF 480000 20180512_000000 20180512_000000 0

5 V5.2 WRF 480000 20180513_000000 20180513_000000 0

5 V5.2 WRF 480000 20180514_000000 20180514_000000 0

5 V5.2 WRF 480000 20180515_000000 20180515_000000 0

5 V5.2 WRF 480000 20180516_000000 20180516_000000 0

5 V5.2 WRF 480000 20180517_000000 20180517_000000 0

5 V5.2 WRF 480000 20180518_000000 20180518_000000 0

5 V5.2 WRF 480000 20180519_000000 20180519_000000 0

5 V5.2 WRF 480000 20180520_000000 20180520_000000 0

5 V5.2 WRF 480000 20180521_000000 20180521_000000 0

5 V5.2 WRF 480000 20180522_000000 20180522_000000 0 

 OBS_VALID_BEG    OBS_VALID_END FCST_VAR FCST_LEV  ...  FCST_THRESH  \

5 20180506_223000 20180507_013000 APCP_06 A6 ... >=50.0

5 20180507_223000 20180508_013000 APCP_06 A6 ... >=50.0

5 20180508_223000 20180509_013000 APCP_06 A6 ... >=50.0

5 20180509_223000 20180510_013000 APCP_06 A6 ... >=50.0

5 20180510_223000 20180511_013000 APCP_06 A6 ... >=50.0

5 20180511_223000 20180512_013000 APCP_06 A6 ... >=50.0

5 20180512_223000 20180513_013000 APCP_06 A6 ... >=50.0

5 20180513_223000 20180514_013000 APCP_06 A6 ... >=50.0

5 20180514_223000 20180515_013000 APCP_06 A6 ... >=50.0

5 20180515_223000 20180516_013000 APCP_06 A6 ... >=50.0

5 20180516_223000 20180517_013000 APCP_06 A6 ... >=50.0

5 20180517_223000 20180518_013000 APCP_06 A6 ... >=50.0

5 20180518_223000 20180519_013000 APCP_06 A6 ... >=50.0

5 20180519_223000 20180520_013000 APCP_06 A6 ... >=50.0

5 20180520_223000 20180521_013000 APCP_06 A6 ... >=50.0

5 20180521_223000 20180522_013000 APCP_06 A6 ... >=50.0

OBS_THRESH COV_THRESH ALPHA LINE_TYPE TOTAL FY_OY FY_ON FN_OY FN_ON

5 >=50.0 NaN NaN CTC 2677 0 0 0 2677

5 >=50.0 NaN NaN CTC 2678 0 0 0 2678

5 >=50.0 NaN NaN CTC 2678 0 0 0 2678

5 >=50.0 NaN NaN CTC 2672 0 0 1 2671

5 >=50.0 NaN NaN CTC 2668 0 1 0 2667

5 >=50.0 NaN NaN CTC 2670 0 0 0 2670

5 >=50.0 NaN NaN CTC 2672 0 0 0 2672

5 >=50.0 NaN NaN CTC 2670 0 0 0 2670

5 >=50.0 NaN NaN CTC 2671 0 0 0 2671

5 >=50.0 NaN NaN CTC 2670 0 0 0 2670

5 >=50.0 NaN NaN CTC 2674 0 0 0 2674

5 >=50.0 NaN NaN CTC 2673 0 0 0 2673

5 >=50.0 NaN NaN CTC 2671 0 2 0 2669

5 >=50.0 NaN NaN CTC 2672 0 1 0 2671

5 >=50.0 NaN NaN CTC 2671 0 0 1 2670

5 >=50.0 NaN NaN CTC 2671 0 0 0 2671

[16 rows x 26 columns]

df.mean(axis=0,skipna=False)函数输出结果是这样
Series([], dtype: float64)

最奇怪的是另一个df就没问题
下面是另一个df长这样：
VERSION MODEL FCST_LEAD FCST_VALID_BEG FCST_VALID_END OBS_LEAD \
5 V5.2 WRF 480000 20180507_000000 20180507_000000 0

5 V5.2 WRF 480000 20180508_000000 20180508_000000 0

5 V5.2 WRF 480000 20180509_000000 20180509_000000 0

5 V5.2 WRF 480000 20180510_000000 20180510_000000 0

5 V5.2 WRF 480000 20180511_000000 20180511_000000 0

5 V5.2 WRF 480000 20180512_000000 20180512_000000 0

5 V5.2 WRF 480000 20180513_000000 20180513_000000 0

5 V5.2 WRF 480000 20180514_000000 20180514_000000 0

5 V5.2 WRF 480000 20180515_000000 20180515_000000 0

5 V5.2 WRF 480000 20180516_000000 20180516_000000 0

5 V5.2 WRF 480000 20180517_000000 20180517_000000 0

5 V5.2 WRF 480000 20180518_000000 20180518_000000 0

5 V5.2 WRF 480000 20180519_000000 20180519_000000 0

5 V5.2 WRF 480000 20180520_000000 20180520_000000 0

5 V5.2 WRF 480000 20180521_000000 20180521_000000 0

5 V5.2 WRF 480000 20180522_000000 20180522_000000 0 

 OBS_VALID_BEG    OBS_VALID_END FCST_VAR FCST_LEV    ...     EDI_BCL  \

5 20180506_223000 20180507_013000 APCP_06 A6 ... NaN

5 20180507_223000 20180508_013000 APCP_06 A6 ... NaN

5 20180508_223000 20180509_013000 APCP_06 A6 ... NaN

5 20180509_223000 20180510_013000 APCP_06 A6 ... NaN

5 20180510_223000 20180511_013000 APCP_06 A6 ... NaN

5 20180511_223000 20180512_013000 APCP_06 A6 ... NaN

5 20180512_223000 20180513_013000 APCP_06 A6 ... NaN

5 20180513_223000 20180514_013000 APCP_06 A6 ... NaN

5 20180514_223000 20180515_013000 APCP_06 A6 ... NaN

5 20180515_223000 20180516_013000 APCP_06 A6 ... NaN

5 20180516_223000 20180517_013000 APCP_06 A6 ... NaN

5 20180517_223000 20180518_013000 APCP_06 A6 ... NaN

5 20180518_223000 20180519_013000 APCP_06 A6 ... NaN

5 20180519_223000 20180520_013000 APCP_06 A6 ... NaN

5 20180520_223000 20180521_013000 APCP_06 A6 ... NaN

5 20180521_223000 20180522_013000 APCP_06 A6 ... NaN

EDI_BCU SEDI SEDI_NCL SEDI_NCU SEDI_BCL SEDI_BCU BAGSS BAGSS_BCL BAGSS_BCU

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

5 NaN NaN NaN NaN NaN NaN NaN NaN NaN

[16 rows x 114 columns]

df.mean()的输出结果长这样
COV_THRESH NaN
ALPHA 0.050000
BASER 0.000047
BASER_NCL 0.000008
BASER_NCU 0.001521
BASER_BCL 0.000000
BASER_BCU 0.000140
FMEAN 0.000094
FMEAN_NCL 0.000021
FMEAN_NCU 0.001601
FMEAN_BCL 0.000000
FMEAN_BCU 0.000257
ACC 0.999861
ACC_NCL 0.998312
ACC_NCU 0.999969
ACC_BCL 0.999603
ACC_BCU 1.000000

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1条回答 默认 最新

  • dabocaiqq 2018-05-27 02:35
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    https://blog.csdn.net/u010383605/article/details/78879515

    本回答被题主选为最佳回答 , 对您是否有帮助呢?
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