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 9pandas 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 9create dataframe panndas
import pandas as pd
data = {'First Column Name': ['First value', 'Second value',...],
'Second Column Name': ['First value', 'Second value',...],
....
}
df = pd.DataFrame (data, columns = ['First Column Name','Second Column Name',...])
print (df)creating a pandas df
>>> d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
col1 col2
0 1 3
1 2 4pandas dataframe
>>> df2 = pd.DataFrame(np.array([[23, 99, 78], [65, 95, 90], [90, 98, 96]]),
... columns=['krish', 'ishwar', 'raj'])
>>> df2
a b c
0 1 2 3
1 4 5 6
2 7 8 9data 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 7Copyright © 2021 Codeinu
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