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 9creata daframe python
d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)
dfcreate 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})pandas dataframe
d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
col1 col2
0 1 3
1 2 4dataframein 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 femaleCopyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
