Panda Numpy 将数据转换为列

Question

I have a data result that when I print it looks like

  >>>print(result)

   [[0]
    [1]
    [0]
    [0]
    [1]
    [0]]

I guess that's about the same as [ [0][1][0][0][1][0] ] which seems a bit weird [0,1,0,0,1,0] seems a more logical representation but somehow it's not like that.

Though I would like these values to be added as a single column to a Panda dataframe df

I tried several ways to join it to my dataframe:

 df = pd.concat(df,result)
 df = pd.concat(df,{'result' =result})
 df['result'] =pd.aply(result, axis=1)

with no luck. How can I do it?

Answer 1

如果您希望将该数组放入平面格式的 Pandas 数据框列中，以下是最简单的方法： df["result"] = sum(result, [])

Answer 2

There is multiple ways for flatten your data:

df = pd.DataFrame(data=np.random.rand(6,2))

result = np.array([0,1,0,0,1,0])[:, None]
print (result)
[[0]
 [1]
 [0]
 [0]
 [1]
 [0]]


df['result'] = result[:,0]
df['result1'] = result.ravel()
#df['result1'] = np.concatenate(result)

print (df)
          0         1  result  result1
0  0.098767  0.933861       0        0
1  0.532177  0.610121       1        1
2  0.288742  0.718452       0        0
3  0.520980  0.367746       0        0
4  0.253658  0.011994       1        1
5  0.662878  0.846113       0        0

Answer 3

As long as the number of data points in this list is the same as the number of rows of the dataframe this should work:

import pandas as pd

your_data = [[0],[1],[0],[0],[1],[0]]

df = pd.DataFrame() # skip and use your own dataframe with len(df) == len(your_data)
df['result'] = [i[0] for i in your_data]