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 9dataframein python
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',...])define a dataframe using pandas
In [2]: df = pd.DataFrame(
...: {
...: "Name": [
...: "Braund, Mr. Owen Harris",
...: "Allen, Mr. William Henry",
...: "Bonnell, Miss. Elizabeth",
...: ],
...: "Age": [22, 35, 58],
...: "Sex": ["male", "male", "female"],
...: }
...: )
...:
In [3]: df
Out[3]:
Name Age Sex
0 Braund, Mr. Owen Harris 22 male
1 Allen, Mr. William Henry 35 male
2 Bonnell, Miss. Elizabeth 58 femaledata 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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