从熊猫数据框中提取单列有两种方法,区别是什么?[副本]

df = floor_temperatures.join(power_consumption, how='outer').join(outside_temperatures, how='outer')
df = df.resample('5Min').mean()
print (df)

                           floor_temperature  power_consumption  outside_temperature
timestamp
2019-01-23 00:00:00+00:00           8.350000           0.045000           -11.388889
...                                      ...                ...                  ...
2019-01-24 07:25:00+00:00          10.400000           0.060000            -8.900000
[407 rows x 3 columns]

然后我基于一列创建一个新的数据帧,如下所示:

y = df[['floor_temperature']]
print("1:")
print (y)

1:
                           floor_temperature
timestamp
2019-01-23 00:00:00+00:00           8.350000
2019-01-23 02:25:00+00:00           8.600000
...                                      ...
2019-01-24 07:25:00+00:00          10.400000
[407 rows x 1 columns]

print("2:")
y = df['floor_temperature']
print (y)

2:
timestamp
2019-01-23 00:00:00+00:00     8.350000
                               ...
2019-01-24 07:25:00+00:00    10.400000
Freq: 5T, Name: floor_temperature, Length: 407, dtype: float64

为什么最后两个DataFrame对象的打印略有不同?

第一个页脚为“[407行x 1列]”,第二个页脚为“Freq:5T,Name:floor\u temperature,Length:407,dtype:float64”。