Hello. I'm pre-processing the Pandas data frame data, but I'm inquiring because there's a blockage.

What I want to do first is to combine three days of data into one Row per Oper, as shown in

After that, I want to make the same type of data frame as the data of Oper2 enters the second Row, but I am inquiring because it is not as well made as I thought. I want to make a 10 x 78 Dataset I didn't know how to handle the index, so it became 1 x 780. I'd appreciate it if you could help me, masters.

```
df = pd.DataFrame()
for i in range(0,10):
for j in range(0,3):
result = data1[j:j+1]
result = result.reset_index(drop=True)
df = pd.concat([df,result], ignore_index = True,axis=1)
```

2022-09-20 15:07

```
Python 3.8.5 (tags/v3.8.5:580fbb0, Jul 20 2020, 15:57:54) [MSC v.1924 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license()" for more information.
>>> import pandas as pd
>>> df = pd.DataFrame({"a":[1,2,3,4,5,6], "b":list("abcdef")})
>>> df
a b
0 1 a
1 2 b
2 3 c
3 4 d
4 5 e
5 6 f
>>> df[0::3]
a b
0 1 a
3 4 d
>>> df[1::3]
a b
1 2 b
4 5 e
>>> df[2::3]
a b
2 3 c
5 6 f
>>> pd.concat([df[0::3], df[1::3], df[2::3]], axis=1)
a b a b a b
0 1.0 a NaN NaN NaN NaN
1 NaN NaN 2.0 b NaN NaN
2 NaN NaN NaN NaN 3.0 c
3 4.0 d NaN NaN NaN NaN
4 NaN NaN 5.0 e NaN NaN
5 NaN NaN NaN NaN 6.0 f
>>> df[0::3].reset_index(drop=True)
a b
0 1 a
1 4 d
>>> df[1::3].reset_index(drop=True)
a b
0 2 b
1 5 e
>>> df[2::3].reset_index(drop=True)
a b
0 3 c
1 6 f
>>> pd.concat([df[0::3].reset_index(drop=True), df[1::3].reset_index(drop=True), df[2::3].reset_index(drop=True)], axis=1)
a b a b a b
0 1 a 2 b 3 c
1 4 d 5 e 6 f
>>>
```

2022-09-20 15:07

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