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
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.
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