["python","pandas","dataframe","list","numpy"]
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 = np.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.
Specify data, index and columns to the DataFrame constructor, as follows: >>> 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 As @joris mentions, you may need to change above to np.int_(data[1:,1:]) to have the correct data type.