Pandas dataframe

>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
...                    columns=['a', 'b', 'c'])
>>> df2
   a  b  c
0  1  2  3
1  4  5  6
2  7  8  9

Source: pandas.pydata.org

Create a dataframe python

import numpy as np
import pandas as pd
vect1=np.zeros(10)
vect2=np.ones(10)
df=pd.DataFrame({'col1':vect1,'col2':vect2})

Creata daframe python

d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)
df

Source: pandas.pydata.org

Pandas dataframe

d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
   col1  col2
0     1     3
1     2     4

Source: pandas.pydata.org

Data frame

>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],
...                 dtype=[("a", "i4"), ("b", "i4"), ("c", "i4")])
>>> df3 = pd.DataFrame(data, columns=['c', 'a'])
...
>>> df3
   c  a
0  3  1
1  6  4
2  9  7

Source: pandas.pydata.org

Dataframe in python

# Python code demonstrate creating 
# DataFrame from dict narray / lists 
# By default addresses.
 
import pandas as pd
 
# intialise data of lists.
data = {'Name':['Tom', 'nick', 'krish', 'jack'],
        'Age':[20, 21, 19, 18]}
 
# Create DataFrame
df = pd.DataFrame(data)
 
# Print the output.
print(df)

Source: geeksforgeeks.org

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