我有两个数据框。一个有一组对应于特定时间和日期的值 ( df_1
)。另一个有一组对应于特定日期的值 ( df_2
)。我想合并这些 DataFrame,以便将df_2
for 日期的值应用于相应日期的所有时间。df_1
所以,这里是df_1
:
|DatetimeIndex |value_1|
|-----------------------|-------|
|2015-07-18 13:53:33.280|10 |
|2015-07-18 15:43:30.111|11 |
|2015-07-19 13:54:03.330|12 |
|2015-07-20 13:52:13.350|13 |
|2015-07-20 16:10:01.901|14 |
|2015-07-20 16:50:55.020|15 |
|2015-07-21 13:56:03.126|16 |
|2015-07-22 13:53:51.747|17 |
|2015-07-22 19:45:14.647|18 |
|2015-07-23 13:53:29.346|19 |
|2015-07-23 20:00:30.100|20 |
这是df_2
:
|DatetimeIndex|value_2|
|-------------|-------|
|2015-07-18 |100 |
|2015-07-19 |200 |
|2015-07-20 |300 |
|2015-07-21 |400 |
|2015-07-22 |500 |
|2015-07-23 |600 |
我想像这样合并它们:
|DatetimeIndex |value_1|value_2|
|-----------------------|-------|-------|
|2015-07-18 00:00:00.000|NaN |100 |
|2015-07-18 13:53:33.280|10.0 |100 |
|2015-07-18 15:43:30.111|11.0 |100 |
|2015-07-19 00:00:00.000|NaN |200 |
|2015-07-19 13:54:03.330|12.0 |200 |
|2015-07-20 00:00:00.000|NaN |300 |
|2015-07-20 13:52:13.350|13.0 |300 |
|2015-07-20 16:10:01.901|14.0 |300 |
|2015-07-20 16:50:55.020|15.0 |300 |
|2015-07-21 00:00:00.000|NaN |400 |
|2015-07-21 13:56:03.126|16.0 |400 |
|2015-07-22 00:00:00.000|NaN |500 |
|2015-07-22 13:53:51.747|17 |500 |
|2015-07-22 19:45:14.647|18 |500 |
|2015-07-23 00:00:00.000|NaN |600 |
|2015-07-23 13:53:29.346|19 |600 |
|2015-07-23 20:00:30.100|20 |600 |
所以,value_2
存在于整个日子。
这叫什么合并?怎么做到呢?
DataFrames 的代码如下:
import pandas as pd
df_1 = pd.DataFrame(
[
[pd.Timestamp("2015-07-18 13:53:33.280"), 10],
[pd.Timestamp("2015-07-18 15:43:30.111"), 11],
[pd.Timestamp("2015-07-19 13:54:03.330"), 12],
[pd.Timestamp("2015-07-20 13:52:13.350"), 13],
[pd.Timestamp("2015-07-20 16:10:01.901"), 14],
[pd.Timestamp("2015-07-20 16:50:55.020"), 15],
[pd.Timestamp("2015-07-21 13:56:03.126"), 16],
[pd.Timestamp("2015-07-22 13:53:51.747"), 17],
[pd.Timestamp("2015-07-22 19:45:14.647"), 18],
[pd.Timestamp("2015-07-23 13:53:29.346"), 19],
[pd.Timestamp("2015-07-23 20:00:30.100"), 20]
],
columns = [
"datetime",
"value_1"
]
)
df_1.index = df_1["datetime"]
del df_1["datetime"]
df_1.index = pd.to_datetime(df_1.index.values)
df_2 = pd.DataFrame(
[
[pd.Timestamp("2015-07-18 00:00:00"), 100],
[pd.Timestamp("2015-07-19 00:00:00"), 200],
[pd.Timestamp("2015-07-20 00:00:00"), 300],
[pd.Timestamp("2015-07-21 00:00:00"), 400],
[pd.Timestamp("2015-07-22 00:00:00"), 500],
[pd.Timestamp("2015-07-23 00:00:00"), 600]
],
columns = [
"datetime",
"value_2"
]
)
df_2
df_2.index = df_2["datetime"]
del df_2["datetime"]
df_2.index = pd.to_datetime(df_2.index.values)