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
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
dataframe object to numpy array
import pandas as pd
#initialize a dataframe
df = pd.DataFrame(
[[21, 72, 67],
[23, 78, 69],
[32, 74, 56],
[52, 54, 76]],
columns=['a', 'b', 'c'])
#convert dataframe to numpy array
arr = df.to_numpy()
print('nNumpy Arrayn----------n', arr)
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)
convert pandas dataframe to numpy dataframe
DataFrame.to_numpy(dtype=None, copy=False, na_value=<object object>)
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]])
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