python - Pandas read_csv() : keep 0 as 0 (not convert it to NaN)

Question

我正在尝试读取一个 csv 文件，其中的一个示例:

datetime,check,lat,lon,co_alpha,atn,status,bc
2012-10-27 15:00:59,2,0,0,2.427,,,
2012-10-27 15:01:00,2,0,0,2.407,,,
2012-10-27 15:02:49,2,0,0,2.207,-17.358,0,-16162
2012-10-27 15:02:50,2,0,0,2.207,-17.354,0,8192
2012-10-27 15:02:51,1,0,0,2.207,-17.358,0,-8152
2012-10-27 15:02:52,1,0,0,2.207,-17.358,0,648
2012-10-27 15:06:03,0,51.195076,4.444407,2.349,-17.289,0,4909
2012-10-27 15:06:04,0,51.195182,4.44427,2.344,-17.289,0,587
2012-12-05 09:21:34,,,,,42.960,1,16430
2012-12-05 09:21:35,,,,,42.962,1,3597

我遇到的问题是，在只有整数的列中，0 被转换为 NaN(例如列“检查”和“状态”，这些是只有整数的列，但该列被读取为 float ，因为有真正的缺失值)。但我只想将空值转换为 NaN，而不是零。

这是我得到的:

>>> pd.read_clipboard(sep=',', parse_dates=True, index_col=0)
                     check        lat       lon  co_alpha     atn  status     bc
datetime                                                                        
2012-10-27 15:00:59      2   0.000000  0.000000     2.427     NaN     NaN    NaN
2012-10-27 15:01:00      2   0.000000  0.000000     2.407     NaN     NaN    NaN
2012-10-27 15:02:49      2   0.000000  0.000000     2.207 -17.358     NaN -16162
2012-10-27 15:02:50      2   0.000000  0.000000     2.207 -17.354     NaN   8192
2012-10-27 15:02:51      1   0.000000  0.000000     2.207 -17.358     NaN  -8152
2012-10-27 15:02:52      1   0.000000  0.000000     2.207 -17.358     NaN    648
2012-10-27 15:06:03    NaN  51.195076  4.444407     2.349 -17.289     NaN   4909
2012-10-27 15:06:04    NaN  51.195182  4.444270     2.344 -17.289     NaN    587
2012-12-05 09:21:34    NaN        NaN       NaN       NaN  42.960       1  16430
2012-12-05 09:21:35    NaN        NaN       NaN       NaN  42.962       1   3597

因此，在“检查”和“状态”列中，有很多 NaN。在“lat”和“lon”列中，0 不会转换为 NaN。

• 使用 na_values='' 和 keep_default_na=False 没有帮助。有没有办法指定不将 int 0 转换为 NaN？或者这是一个错误？

• 我可以使用 dtype 关键字将特定列的数据类型指定为 int。这使 0 保持为 0，但问题是这些列还包含真正的 NaN(空值)。因此，在这种情况下，这些值也被转换为 0，因为在 int 列中不能有 NaN。出于这个原因，我必须将所有列都保留为 float 。

---

编辑:升级到 pandas 0.10.1 后，即使没有指定 keep_default_na 和 na_values，它也能按预期工作:

>>> pd.read_clipboard(sep=',', parse_dates=True, index_col=0)
                     check        lat       lon  co_alpha     atn  status     bc
datetime                                                                        
2012-10-27 15:00:59      2   0.000000  0.000000     2.427     NaN     NaN    NaN
2012-10-27 15:01:00      2   0.000000  0.000000     2.407     NaN     NaN    NaN
2012-10-27 15:02:49      2   0.000000  0.000000     2.207 -17.358       0 -16162
2012-10-27 15:02:50      2   0.000000  0.000000     2.207 -17.354       0   8192
2012-10-27 15:02:51      1   0.000000  0.000000     2.207 -17.358       0  -8152
2012-10-27 15:02:52      1   0.000000  0.000000     2.207 -17.358       0    648
2012-10-27 15:06:03      0  51.195076  4.444407     2.349 -17.289       0   4909
2012-10-27 15:06:04      0  51.195182  4.444270     2.344 -17.289       0    587
2012-12-05 09:21:34    NaN        NaN       NaN       NaN  42.960       1  16430
2012-12-05 09:21:35    NaN        NaN       NaN       NaN  42.962       1   3597

Answer 1

您必须先将 keep_default_na 设置为 False:

df = pd.read_clipboard(sep=',', index_col=0, keep_default_na=False, na_values='')

In [2]: df
Out[2]: 
                     check        lat       lon  co_alpha     atn  status     bc
datetime                                                                        
2012-10-27 15:00:59      2   0.000000  0.000000     2.427     NaN     NaN    NaN
2012-10-27 15:01:00      2   0.000000  0.000000     2.407     NaN     NaN    NaN
2012-10-27 15:02:49      2   0.000000  0.000000     2.207 -17.358       0 -16162
2012-10-27 15:02:50      2   0.000000  0.000000     2.207 -17.354       0   8192
2012-10-27 15:02:51      1   0.000000  0.000000     2.207 -17.358       0  -8152
2012-10-27 15:02:52      1   0.000000  0.000000     2.207 -17.358       0    648
2012-10-27 15:06:03      0  51.195076  4.444407     2.349 -17.289       0   4909
2012-10-27 15:06:04      0  51.195182  4.444270     2.344 -17.289       0    587
2012-12-05 09:21:34    NaN        NaN       NaN       NaN  42.960       1  16430
2012-12-05 09:21:35    NaN        NaN       NaN       NaN  42.962       1   3597

来自 read_tables 的文档字符串:

keep_default_na : bool, default True
     If na_values are specified and keep_default_na is False the default NaN
    values are overridden, otherwise they're appended to

na_values : list-like or dict, default None
    Additional strings to recognize as NA/NaN. If dict passed, specific per-column NA values