.resample（'W'）仅拾取一列，而子集包含两列

Question

我试图在对两列进行子集设置后对熊猫数据帧重新采样。下面是数据帧的头部。两列都是熊猫系列

temp_2011_clean[['visibility', 'dry_bulb_faren']].head()
                    visibility  dry_bulb_faren
2011-01-01 00:53:00     10.00   51.0
2011-01-01 01:53:00     10.00   51.0
2011-01-01 02:53:00     10.00   51.0
2011-01-01 03:53:00     10.00   50.0
2011-01-01 04:53:00     10.00   50.0

type(temp_2011_clean['visibility'])
pandas.core.series.Series

type(temp_2011_clean['dry_bulb_faren'])
pandas.core.series.Series

虽然.resample（'W'）方法成功地创建了重采样对象，但如果我将.mean（）方法链接到同一个对象，它只拾取一列，而不是预期的两列。有人能提出什么问题吗？为什么少了一列

temp_2011_clean[['visibility', 'dry_bulb_faren']].resample('W')
<pandas.core.resample.DatetimeIndexResampler object at 0x0000016F4B943288>

temp_2011_clean[['visibility', 'dry_bulb_faren']].resample('W').mean().head()
            dry_bulb_faren
2011-01-02  44.791667
2011-01-09  50.246637
2011-01-16  41.103774
2011-01-23  47.194313
2011-01-30  53.486188

Answer 1

我认为问题应该是visibility列不是数字，所以非数字列被排除在外

print (temp_2011_clean.dtypes)
visibility         object
dry_bulb_faren    float64
dtype: object

df = temp_2011_clean[['visibility', 'dry_bulb_faren']].resample('W').mean()
print (df)
            dry_bulb_faren
2011-01-02            50.6

因此，通过^{}和errors='coerce'将列转换为数值，以便将非数值转换为NaN：

temp_2011_clean['visibility'] = pd.to_numeric(temp_2011_clean['visibility'], errors='coerce')

print (temp_2011_clean.dtypes)
visibility        float64
dry_bulb_faren    float64
dtype: object

df = temp_2011_clean[['visibility', 'dry_bulb_faren']].resample('W').mean()
print (df)
            visibility  dry_bulb_faren
2011-01-02        10.0            50.6