Finding entries in a DataFrame that fall above a threshold

Question

In a dataframe as such named pd:

country	1980	1990	2000
India.	800	2000	3500
China	200	2000	1500
UK.	160	150	400

How can we find the rows where the values of year 2000 are greater than 1000?

I see there are two ways:

pd.loc[pd['2000'] > 1000]

and

pd[pd['2000'] > 1000]

is there a difference in the two methods? I see it produces the same results but don't understand if there is a difference.

Thanks

Also this: https://stackoverflow.com/questions/31593201/how-are-iloc-and-loc-different — Dani Mesejo, Jan 05 '21 at 23:38

score 0 · Answer 1 · answered Jan 05 '21 at 23:45

The first case is generally better because the second (indexing the dataframe instead of using df.loc) sometimes returns a copy of data and sometimes returns a view depending on how it's used. The difference is explained here: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html?highlight=assigning%20view#indexing-view-versus-copy

I don't think it matters unless you're assigning to the selection, but as a rule of thumb it's best to use a series of selection criteria in df.loc[], for example pd.loc[(pd['2000'] > 1000), 'columnName']

this is wonderful! That makes sense. It's more of a use by case in a way! — ravidissa, Jan 06 '21 at 01:57

Finding entries in a DataFrame that fall above a threshold

1 Answers1