Answers for "converting a dataframe to numpy array"

convert array to dataframe python

np.random.seed(123)
e = np.random.normal(size=10)  
dataframe=pd.DataFrame(e, columns=['a']) 
print (dataframe)
          a
0 -1.085631
1  0.997345
2  0.282978
3 -1.506295
4 -0.578600
5  1.651437
6 -2.426679
7 -0.428913
8  1.265936
9 -0.866740

e_dataframe=pd.DataFrame({'a':e}) 
print (e_dataframe)
          a
0 -1.085631
1  0.997345
2  0.282978
3 -1.506295
4 -0.578600
5  1.651437
6 -2.426679
7 -0.428913
8  1.265936
9 -0.866740

make pandas df from np array

numpy_data = np.array([[1, 2], [3, 4]])
df = pd.DataFrame(data=numpy_data, index=["row1", "row2"], columns=["column1", "column2"])
print(df)
>>>
  column1  column2
row1        1        2
row2        3        4

numpy arrauy to df

numpy_data = np.array([[1, 2], [3, 4]])
df = pd.DataFrame(data=numpy_data, index=["row1", "row2"], columns=["column1", "column2"])
print(df)

get pandas dataframe as numpy array

>>> df = pd.DataFrame({"A": [1, 2], "B": [3.0, 4.5]})
>>> df.to_numpy()
array([[1. , 3. ],
       [2. , 4.5]])

list dataframe to numpy array

df.values

array([[nan, 0.2, nan],
       [nan, nan, 0.5],
       [nan, 0.2, 0.5],
       [0.1, 0.2, nan],
       [0.1, 0.2, 0.5],
       [0.1, nan, 0.5],
       [0.1, nan, nan]])