Convert Pandas Dataframe Row and Column to Numpy Array

Question

I have created a matrix in dataframe to compare words and have converted it to numpy using "penaltymatrix = np.array(df.values)". How do I convert the rows and columns also?

current output

The top part is the numpy array and the second part is the pandas dataframe which includes the appropiate column & row names.

Code:

def computeTable():
    sampInput = file1()
    refInput = file2()
    sampString = [word.strip(string.punctuation).lower() for word in sampInput.split()]
    refString = [word.strip(string.punctuation).lower() for word in refInput.split()]
    df = pd.DataFrame(index=sampString, columns=refString)


    penaltymatrix = np.array(df.values)
    penaltymatrix[0, 0] = 0
    print(penaltymatrix)
    print(3*"\n")
    print(df)

can you also tell us how your desired output should look? i mean if you want the headers of columns in dataframe as a list? — khaldi
– khaldi, Commented Jul 19, 2018 at 9:58
seems like you want index and columns also, use df.columns and df.index to get them — Sreekiran A R
– Sreekiran A R, Commented Jul 19, 2018 at 10:03
I need to write code to formulaically generate the table. I don't necessarily need the headers to show but I need to be able to manipulate specific elements. — Brndn
– Brndn, Commented Jul 19, 2018 at 10:03

Massoud · Accepted Answer · 2018-07-19 10:21:20Z

0

Here is what you want:

def computeTable():
    sampInput = file1()
    refInput = file2()
    sampString = [word.strip(string.punctuation).lower() for word in sampInput.split()]
    refString = [word.strip(string.punctuation).lower() for word in refInput.split()]
    df = pd.DataFrame(index=sampString, columns=refString)

    penaltymatrix = np.hstack([np.array([0]+list(df.index)).reshape((-1, 1)), np.vstack([np.array(df.columns), df.values])])
    print(penaltymatrix)
    print(3*"\n")
    print(df)

answered Jul 19, 2018 at 10:21

Massoud

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