filter dataframe columns as you iterate through rows and create dictionary - python-3.x

Question

I have the following table of data in a spreadsheet:
Name Description Value
foo foobar 5
baz foobaz 4
bar foofoo 8
I'm reading the spreadsheet and passing the data as a dataframe.
I need to transform this table of data to json following a specific schema.
I have the following script:
for index, row in df.iterrows():
if row['Description'] == 'foofoo':
print(row.to_dict())
which return:
{'Name': 'bar', 'Description': 'foofoo', 'Value': '8'}
I want to be able to filter out a specific column. For example, to return this:
{'Name': 'bar', 'Description': 'foofoo'}
I know that I can print only the columns I want with this print(row['Name'],row['Description']) however this is only returning me values when I also want to return the key.
How can I do this?

Answer 1

I wrote this entire thing only to realize that #anky_91 had already suggested it. Oh well...
import pandas as pd
data = {
"name": ["foo", "abc", "baz", "bar"],
"description": ["foobar", "foofoo", "foobaz", "foofoo"],
"value": [5, 3, 4, 8],
}
df = pd.DataFrame(data=data)
print(df, end='\n\n')
rec_dicts = df.loc[df["description"] == "foofoo", ["name", "description"]].to_dict(
"records"
)
print(rec_dicts)
Output:
name description value
0 foo foobar 5
1 abc foofoo 3
2 baz foobaz 4
3 bar foofoo 8
[{'name': 'abc', 'description': 'foofoo'}, {'name': 'bar', 'description': 'foofoo'}]

Answer 2

After converting to dictionary you can delete the key which you don't need with:
del(row[value])
Now the dictionary will have only name and description.

Answer 3

You can try this:
import io
import pandas as pd
s="""Name,Description,Value
foo,foobar,5
baz,foobaz,4
bar,foofoo,8
"""
df = pd.read_csv(io.StringIO(s))
for index, row in df.iterrows():
if row['Description'] == 'foofoo':
print(row[['Name', 'Description']].to_dict())
Result:
{'Name': 'bar', 'Description': 'foofoo'}