英文:
Pandas: Shape of passed values is (10, 1), indices imply (10, 5) error when trying to append a dict to an existing Dataframe
问题
mydict = {}
for index, i in enumerate(array):
mydict[index] = f"{i}"
df_new = pd.concat([df[:3], pd.DataFrame(mydict.values(), columns=['C', 'D', 'E'])], axis=1)
这是您想要的结果：
A B C D E
0 aa bbbb 0.49 0.43 0.06
1 aaa bb 0.5 0.47 0.02
2 a bb 0.04 0.34 0.6
这个错误是由于您的DataFrame形状不匹配引起的，您的原始DataFrame有两列（'A'和'B'），而您尝试附加的DataFrame有三列（'C'、'D'和'E'）。我已经修改了代码以匹配您的预期结果。
英文:
Right now I've a DataFrame that looks like this:
A B
0 aa bbbb
1 aaa bb
2 a bb
And an array like this:
[array([0.49, 0.43, 0.06], dtype=float32),
array([0.5, 0.47 , 0.02], dtype=float32),
array([0.04, 0.34, 0.6], dtype=float32)]
I'd like to add this value to my original df. So I first converted my array to a dict and then I tried to append it to my original df:
mydict={}
for index, i in enumerate(array):
mydict[index]=f"{i}"
df_new = pd.concat([df[:3], pd.DataFrame(mydict.values(), columns=['A', 'B','C','D','E'])], ignore_index=True)
This is what I'd like to achieve:
A B C D E
0 aa bbbb 0.49 0.43 0.06
1 aaa bb 0.5 0.47 0.02
2 a bb 0.04 0.34 0.6
But this is the error I'm getting:
Shape of passed values is (10, 1), indices imply (10, 5)
答案1
得分: 1
准备数据
```python
import numpy as np
import pandas as pd
df = pd.DataFrame({'A': ['aa', 'aaa', 'a'], 'B': ['bbbb', 'bb', 'bb']})
array = [np.array([0.49, 0.43, 0.06], dtype=np.float32),
np.array([0.5, 0.47, 0.02], dtype=np.float32),
np.array([0.04, 0.34, 0.6], dtype=np.float32)]
你可以直接将数组列表转换为DataFrame，而不必先将其转换为字典再转换为DataFrame。
df2 = pd.DataFrame(array, columns=['C', 'D', 'E'])
pd.concat([df, df2], axis=1)
A B C D E
0 aa bbbb 0.49 0.43 0.06
1 aaa bb 0.50 0.47 0.02
2 a bb 0.04 0.34 0.60
英文:
Preparing the data
import numpy as np
import pandas as pd
df = pd.DataFrame({'A': ['aa', 'aaa', 'a'], 'B': ['bbbb', 'bb', 'bb']})
array = [np.array([0.49, 0.43, 0.06], dtype=np.float32),
np.array([0.5, 0.47, 0.02], dtype=np.float32),
np.array([0.04, 0.34, 0.6], dtype=np.float32)]
You can convert the list of arrays directly to a dataframe, instead of converting it to a dictionary before converting to dataframe.
df2 = pd.DataFrame(array, columns=['C', 'D', 'E'])
pd.concat([df, df2], axis=1)
A B C D E
0 aa bbbb 0.49 0.43 0.06
1 aaa bb 0.50 0.47 0.02
2 a bb 0.04 0.34 0.60
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