different output from pandas iterrows if .csv column headed “name” than other text

i’m a beginner using pandas to look at a csv. i’m using .iterrows() to see if a given record matches today’s date, so far so good. however when calling (row.name) for a .csv with a column headed ‘name’ i get different output than if i rename the column and edit the (row.”column-heading”) to match. i can call it anything but “name” and get the right output. i tried (row.notthename) (row.fish) and (row.thisisodd) – which all worked fine – before coming here.

if the first colmumn in birthdays.csv is “name” and i call print(row.name) it returns “2”. if the first column is “notthename” and i call print(row.notthename) it returns the relevant name. what gives? i don’t understand why arbitrarily renaming the column and the function call is yielding different output?

eg case A: column named “name”

birthdays.csv:
name,email,year,month,day
a test name,test@email.com,1961,12,21
testerito,blagh@sdgdg.com,1985,02,23
testeroonie,sihgfdb@sidkghsb.com,2022,01,17

data = pandas.read_csv("birthdays.csv")
for (index, row) in data.iterrows():
    if (dt.datetime.now()).month == row.month and (dt.datetime.now()).day == row.day:
        print(row.name)

outputs “2”

whereas case B: column named “notthename”

data = pandas.read_csv("birthdays.csv")
for (index, row) in data.iterrows():
    if (dt.datetime.now()).month == row.month and (dt.datetime.now()).day == row.day:
        print(row.notthename)

outputs “testeroonie”

i’m missing something…. is there some special handling of “name” going on?

thanks for helping me learn!

Answer

This happens because DataFrame.iterrows returns a Series object, and the Series object has a built-in property called name. This is why using the object shortcut for column names, although convenient, can be dangerous. The dictionary notation doesn’t have this issue:

    print(row['name'])

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Answer