pandas 将二维 numpy 数组转换为数据帧行
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Converting a 2D numpy array to dataframe rows
提问by i.n.n.m
I have a list of list that I would like to make it as a row. The closest I got was using this post. However, I could not get my answer.
我有一个列表列表，我想把它排成一行。我得到的最接近的是使用这篇文章。但是，我无法得到我的答案。
For example lets say I have a testarrayof values,
例如，假设我有一个testarray值，
([[ 26.85406494],
[ 27.85406494],
[ 28.85406494],
[ 29.85406494],
[ 30.85406494],
[ 31.85406494],
[ 32.85406494],
[ 33.85406494],
[ 34.85406494],
[ 35.85406494],
[ 36.85406494],
[ 37.85406494],
[ 38.85406494],
[ 39.85406494],
[ 40.85406494],
[ 41.85406494]])
I need like as a pandasDataFrame row like this,
我需要像这样的pandasDataFrame 行，
Row_value
0 26.85406494
1 27.85406494
2 29.85406494
...
I tried the following,
我尝试了以下，
df = pd.DataFrame({'Row_value':testarray})
I get an error,
我收到一个错误，
ValueError: If using all scalar values, you must pass an index
ValueError：如果使用所有标量值，则必须传递索引
How can I pass those values with an index?
如何通过索引传递这些值？
回答by jezrael
Use DataFrame constructor only with parameter columns:
仅对参数列使用 DataFrame 构造函数：
df = pd.DataFrame(a, columns=['a'])
print (df)
a
0 26.854065
1 27.854065
2 28.854065
3 29.854065
4 30.854065
5 31.854065
6 32.854065
7 33.854065
8 34.854065
9 35.854065
10 36.854065
11 37.854065
12 38.854065
13 39.854065
14 40.854065
15 41.854065
回答by cs95
Try a .reshape(-1, ):
尝试一个.reshape(-1, )：
df = pd.DataFrame({'Row_value':testarray.reshape(-1, )})
df
Row_value
0 26.854065
1 27.854065
2 28.854065
3 29.854065
4 30.854065
5 31.854065
6 32.854065
7 33.854065
8 34.854065
9 35.854065
10 36.854065
11 37.854065
12 38.854065
13 39.854065
14 40.854065
15 41.854065
It looks like your testarrayis a 2D array with 1 column. Convert it to a 1D array.
看起来你testarray是一个 1 列的二维数组。将其转换为一维数组。
The alternative is to not pass a dictionary, but instead pass testarrayas is, like in jezrael's answer.
另一种方法是不传递字典，而是testarray按原样传递，就像在 jezrael 的回答中一样。
