Creating a Pandas DataFrame from a Numpy array: How do I specify the index column and column headers?

I have a Numpy array consisting of a list of lists, representing a two-dimensional array with row labels and column names as shown below:

    data = array([['','Col1','Col2'],['Row1',1,2],['Row2',3,4]])

I'd like the resulting DataFrame to have Row1 and Row2 as index values, and Col1, Col2 as header values

I can specify the index as follows:

    df = pd.DataFrame(data,index=data[:,0]),

however I am unsure how to best assign column headers.

You need to specify data, index and columns to DataFrame constructor, as in:

    >>> pd.DataFrame(data=data[1:,1:],    # values
    ...              index=data[1:,0],    # 1st column as index
    ...              columns=data[0,1:])  # 1st row as the column names

edit : as in the @joris comment, you may need to change above to np.int_(data[1:,1:]) to have correct data type.

From: stackoverflow.com/q/20763012

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