I created the following Series and DataFrame:
import pandas as pd
Series_1 = pd.Series[{'Name': 'Adam','Item': 'Sweet','Cost': 1}]
Series_2 = pd.Series[{'Name': 'Bob','Item': 'Candy','Cost': 2}]
Series_3 = pd.Series[{'Name': 'Cathy','Item': 'Chocolate','Cost': 3}]`
df = pd.DataFrame[[Series_1,Series_2,Series_3], index=['Store 1', 'Store 2', 'Store 3']]
I want to display/print out just one column from the DataFrame [with or without the header row]:
Either
Adam
Bob
Cathy
Or:
Sweet
Candy
Chocolate
I have tried the following code which did not work:
print[df['Item']]
print[df.loc['Store 1']]
print[df.loc['Store 1','Item']]
print[df.loc['Store 1','Name']]
print[df.loc[:,'Item']]
print[df.iloc[0]]
Can I do it in one simple line of code?
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In this article, we will discuss how to select a single column in a data frame. Now let us try to implement this using Python.
First, let’s create a dataframe
Python3
import
pandas as pd
df
=
pd.DataFrame[{
'name'
: [
'Akash'
,
'Ayush'
,
'Ashish'
,
'Diksha'
,
'Shivani'
],
'Age'
: [
21
,
25
,
23
,
22
,
18
],
'Interest'
: [
'Coding'
,
'Playing'
,
'Drawing'
,
'Akku'
,
'Swimming'
]}]
print
[
"The original data frame"
]
df
Output:
Method 1: Using Dot[dataframe.columnname] returns the complete selected column
Python3
print
[
"Single column value using dataframe.dot"
]
print
[df.Interest]
Output:
Method 2: Using dataframe[columnname] method:
There are some problems that may occur with using dataframe.dot are as follows:
- Through dot method, we cannot Select column names with spaces.
- Ambiguity may occur when we Select column names that have the same name as methods for example max method of dataframe.
- We cannot Select multiple columns using dot method.
- We cannot Set new columns using dot method.
Because of the above reason dataframe[columnname] method is used widely.
Python3
print
[
"Single column value using dataframe[]"
]
print
[df[
'Interest'
]]
Output:
Another Example now if we want to select the column Age.
Python3
print
[
"Single column value using dataframe[]"
]
print
[df[
'Age'
]]
Output: