How to convert 1 column dataframe to 8 column-CodePudding

How can I convert a 1-column dataframe array (in python) to an 8 column dataframe?

I have tried to use Numpy reshape function as follows:

    data = []
    for x in range(0, 24):
        data.append(x)

    df = pd.DataFrame(data)
    reshaped = pd.DataFrame(np.reshape(df.columns.to_numpy(), (1, 8)), columns=["Heading1", "Heading2", "Heading3", "Heading4", "Heading5", "Heading6", "Heading7", "Heading8"])

but when doing so, I get the following error:

ValueError: cannot reshape array of size 1 into shape (8)

So, I'm expecting an output of 3 rows x 8 columns of numbers between 0 and 24

Do you have any suggestions?

CodePudding user response：

I'm making some assumptions about what you are after, namely a 8 columns with 3 rows where your original range is spread sequentially across the new shorter rows.

reshaped = pd.DataFrame(np.reshape(df.to_numpy(), (3, 8)), columns=["Heading1", "Heading2", "Heading3", "Heading4", "Heading5", "Heading6", "Heading7", "Heading8"])

   Heading1  Heading2  Heading3  Heading4  Heading5  Heading6  Heading7  \
0         0         1         2         3         4         5         6   
1         8         9        10        11        12        13        14   
2        16        17        18        19        20        21        22   

   Heading8  
0         7  
1        15  
2        23

Two big differences here:

We don't want a numpy array made up of the dataframe's columns. We want one of the whole 1x24 dataframe. So just df.to_numpy()
The shape of the outputted reshaped numpy array has to share the same multiple as the original 1*24 != 1*8, instead we need a 3 by 8 sized array.

CodePudding user response：

Try this:

data = np.arange(24)
df = pd.DataFrame(data, columns=['value'])

new_data = np.array(df['value']).reshape(-1, 8)

new_df = pd.DataFrame(new_data)
new_df.columns = ["Heading1", "Heading2", "Heading3", "Heading4", "Heading5", "Heading6", "Heading7", "Heading8"]

Output:


Heading1    Heading2    Heading3    Heading4    Heading5    Heading6    Heading7    Heading8
0   0   1   2   3   4   5   6   7
1   8   9   10  11  12  13  14  15
2   16  17  18  19  20  21  22  23