select DF columns python
df = df.iloc[:,0:2]
df = df[['column1', 'column2']]select DF columns python
df = df.iloc[:,0:2]
df = df[['column1', 'column2']]select columns pandas
df1 = df.iloc[:,0:2] # Remember that Python does not slice inclusive of the ending index.Select a Column in pandas data Frame notation
df.favorite foodSelect a Column in pandas data Frame
>>> import pandas as pd>>> df = pd.read_csv('data/sample_data.csv', index_col=0)>>> dfselect subset of columns from dataframe
In [25]: titanic.iloc[9:25, 2:5]
Out[25]:
Pclass Name Sex
9 2 Nasser, Mrs. Nicholas (Adele Achem) female
10 3 Sandstrom, Miss. Marguerite Rut female
11 1 Bonnell, Miss. Elizabeth female
12 3 Saundercock, Mr. William Henry male
13 3 Andersson, Mr. Anders Johan male
.. ... ... ...
20 2 Fynney, Mr. Joseph J male
21 2 Beesley, Mr. Lawrence male
22 3 McGowan, Miss. Anna "Annie" female
23 1 Sloper, Mr. William Thompson male
24 3 Palsson, Miss. Torborg Danira female
[16 rows x 3 columns]select columns in pandas df
In [8]: age_sex = titanic[["Age", "Sex"]]
In [9]: age_sex.head()
Out[9]:
Age Sex
0 22.0 male
1 38.0 female
2 26.0 female
3 35.0 female
4 35.0 maleCopyright © 2021 Codeinu
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