python 将两组时间序列中不同数据 按照日期 降序上下合并连接 ?

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import pandas as pd
print("数据1")
grades_df1 = pd.DataFrame(data=
{'日期': ["2022-01-01", "2022-01-02", "2022-01-03", "2022-01-04", "2022-01-05", "2022-01-06", "2022-01-07", "2022-01-08", "2022-01-10","2022-01-11"],
'exam1': [24, 63, 56, 56, 67, 51, 79, 46, 72, 60]})
print(grades_df1)
print(type(grades_df1))
"""
数据1
日期 exam1
0 2022-01-01 24
1 2022-01-02 63
2 2022-01-03 56
3 2022-01-04 56
4 2022-01-05 67
5 2022-01-06 51
6 2022-01-07 79
7 2022-01-08 46
8 2022-01-10 72
9 2022-01-11 60
<class 'pandas.core.frame.DataFrame'>
"""

print("数据2")
grades_df2 = pd.DataFrame(data=
{'日期': ["2022-01-01", "2022-01-02", "2022-01-03", "2022-01-04", "2022-01-05", "2022-01-06", "2022-01-07", "2022-01-08", "2022-01-09","2022-10-01"],
'exam2': [24, 63, 56, 56, 67, 51, 79, 46, 7, 60]})
print(grades_df2)
print(type(grades_df2))
print("数据2")
"""
数据2
日期 exam2
0 2022-01-01 24
1 2022-01-02 63
2 2022-01-03 56
3 2022-01-04 56
4 2022-01-05 67
5 2022-01-06 51
6 2022-01-07 79
7 2022-01-08 46
8 2022-01-09 7
9 2022-10-01 60
<class 'pandas.core.frame.DataFrame'>
"""

# 希望的结果
"""
日期 exam1
0 2022-01-01 24
1 2022-01-02 63
2 2022-01-03 56
3 2022-01-04 56
4 2022-01-05 67
5 2022-01-06 51
6 2022-01-07 79
7 2022-01-08 46
8 2022-10-01 60
9 2022-01-10 72
10 2022-10-11 60
<class 'pandas.core.frame.DataFrame'>
"""

'''

实际数据为多个数据集设置使用动态变量两两合并, 每个数据集都含有多个列, 代码尽量不要太多,太繁琐.

'''

##谢谢

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关键词：python 时间序列 Dataframe import pandas

相关内容：Python数据合并

这个真不知道，不好意思

pd.concat()或者pd.append()方法试试

grades_df2.rename(columns={'exam2':'exam1'},inplace=True)
temp = grades_df1.append(grades_df2)
temp.sort_values(by='日期').drop_duplicates().reset_index(drop=True)

先合并后排序

1. pd.concat([grades_df1,grades_df1]).sort_values('日期',ascending = False)

复制代码

顺一提，论坛的帖子编辑器是有些代码的功能的，直接贴文本看起来比较乱

Studio-R 发表于 2023-6-28 18:46
顺一提，论坛的帖子编辑器是有些代码的功能的，直接贴文本看起来比较乱

好

Studio-R 发表于 2023-6-28 18:45
先合并后排序

谢谢

# 整理好 代码如有需要直接拷贝

import pandas as pd
print("数据1")
grades_df1 = pd.DataFrame(data=
{'日期': ["2022-01-01", "2022-01-02", "2022-01-03", "2022-01-04", "2022-01-05", "2022-01-06", "2022-01-07", "2022-01-08", "2022-01-10","2022-01-11"],
'exam1': [24, 63, 56, 56, 67, 51, 79, 46, 72, 60]})
print(grades_df1)
print(type(grades_df1))
"""
数据1
           日期  exam1
0  2022-01-01     24
1  2022-01-02     63
2  2022-01-03     56
3  2022-01-04     56
4  2022-01-05     67
5  2022-01-06     51
6  2022-01-07     79
7  2022-01-08     46
8  2022-01-10     72
9  2022-01-11     60
<class 'pandas.core.frame.DataFrame'>
"""
import pandas as pd
print("数据2")
grades_df1 = pd.DataFrame(data=
{'日期': ["2022-01-01", "2022-01-02", "2022-01-03", "2022-01-04", "2022-01-05", "2022-01-06", "2022-01-07", "2022-01-08", "2022-01-10","2022-01-11"],
'exam1': [24, 63, 56, 56, 67, 51, 79, 46, 72, 60]})
print(grades_df1)
print(type(grades_df1))
"""
数据2
           日期  exam1
0  2022-01-01     24
1  2022-01-02     63
2  2022-01-03     56
3  2022-01-04     56
4  2022-01-05     67
5  2022-01-06     51
6  2022-01-07     79
7  2022-01-08     46
8  2022-01-10     72
9  2022-01-11     60
<class 'pandas.core.frame.DataFrame'>
"""
print("合并")
# 按日期顺序 降序排列 ascending = True(False) 升降序
df = pd.concat([grades_df1,grades_df1]).sort_values('日期',ascending = False)
print(df)
print(type(df))
"""
合并
           日期  exam1
9  2022-01-11     60
9  2022-01-11     60
8  2022-01-10     72
8  2022-01-10     72
7  2022-01-08     46
7  2022-01-08     46
6  2022-01-07     79
6  2022-01-07     79
5  2022-01-06     51
5  2022-01-06     51
4  2022-01-05     67
4  2022-01-05     67
3  2022-01-04     56
3  2022-01-04     56
2  2022-01-03     56
2  2022-01-03     56
1  2022-01-02     63
1  2022-01-02     63
0  2022-01-01     24
0  2022-01-01     24
<class 'pandas.core.frame.DataFrame'>
"""
# https://bbs.pinggu.org/thread-11525301-1-1.html
# Studio-R

jnutt 发表于 2023-6-28 09:40
grades_df2.rename(columns={'exam2':'exam1'},inplace=True)
temp = grades_df1.append(grades_df2)
te ...

谢谢