import numpy as np
import pandas as pd
my_array = np.array([[11,22,33],[44,55,66]])
df = pd.DataFrame(my_array, columns = ['Column_A','Column_B','Column_C'])
print(df)
print(type(df))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 -0.866740df = pd.DataFrame({"A": [1, 2], "B": [3.0, 4.5]})
>>> df.to_numpy()
array([[1. , 3. ],
[2. , 4.5]])import pandas as pd
df=pd.DataFrame({'col1':vect1,'col2':vect2})numpy_data = np.array([[1, 2], [3, 4]])
df = pd.DataFrame(data=numpy_data, index=["row1", "row2"], columns=["column1", "column2"])
print(df)import numpy as np
import pandas as pd
# Creating a 2 dimensional numpy array
>>> data = np.array([[5.8, 2.8], [6.0, 2.2]])
>>> print(data)
>>> data
array([[5.8, 2.8],
[6. , 2.2]])
# Creating pandas dataframe from numpy array
>>> dataset = pd.DataFrame({'Column1': data[:, 0], 'Column2': data[:, 1]})
>>> print(dataset)
Column1 Column2
0 5.8 2.8
1 6.0 2.2