Selecting Rows in pandas Dataframe based on condition doesnt work

Question

I have a dataframe with a "Timestamp" column like this:

df[Timestamp]

0            1.341709
1            1.343688
2            1.344503
3            1.344593
4            1.344700
              ...    
1263453    413.056745
1263454    413.056836
1263455    413.056945
1263456    413.057046
1263457    413.057153
Name: Timestamp, Length: 1263458, dtype: float64

Now i have two variables to define a start and end of an interval like so:

start = 10
end = 15

To select all rows in the Dataframe where the Timestamp lies between "start" and "end" I use a query approach:

df_want = df.query("@start <= Timestamp < @end")

This gives me a Typeerror though

TypeError: '<=' not supported between instances of 'int' and 'type'

Why does this not work, shouldnt Timestamp be of type 'float64'? Why is it just 'type'?

gtomer · Accepted Answer · 2021-04-30 15:42:40Z

2

You need to do the following:

df_want = df[df['Timestamp'].between(start,end)]

edited Apr 30, 2021 at 15:42

answered Apr 30, 2021 at 15:36

gtomer

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4 Comments

L. argio Over a year ago

Thanks, this works. Any idea, why a normal query approach doesnt do it?

gtomer Over a year ago

I am not familiar with this method in python

Mustafa Aydın Over a year ago

@L.argio It somehow confuses your Timestamp column name with <class 'pandas._libs.tslibs.timestamps.Timestamp'>, hence the error. If you change your column name to, say, timestamp, it should work. I'm not sure if there is any escaping mechanism for this in the query.

L. argio Over a year ago

@MustafaAydın Yes, changing the column name fixes it and query method works. Thank you very much

Mustafa Aydın · Accepted Answer · 2021-04-30 16:33:20Z

0

With the variables

df[(df['Timestamp'] >= start) & (df['Timestamp'] <= end)]

With the values harcoded:

df[(df['Timestamp'] >= 15) & (df['Timestamp'] <= 30)]

edited Apr 30, 2021 at 16:33

Mustafa Aydın

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answered Apr 30, 2021 at 15:37

Alvarodric

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