Reminder: We currently have a dataframe called
measurements and it looks like this:
Sneezes Temperature Humidity Monday 32 10.9 62.5 Tuesday 41 8.2 76.3 Wednesday 56 7.6 82.4 Thursday 62 7.8 98.2 Friday 30 9.4 77.4 Saturday 22 11.1 58.9 Sunday 17 12.4 41.2
To get all available column names, run
We can extract a singular column by using the
Note that the output is a series again
To access a selection of columns, we pass in a list of column names in the desired order
To access given rows you can use the slicing operation as known from lists:
If you pass in a singular number instead of
[start:stop] pandas will look for a row with that number as a label.
This will fail in our example since the rows are not numbered.
loc gives label-based access to the elements of a dataframe.
It follows the pattern
iloc-property works similar to
loc, except that it takes integer-based indexes instead of row/column labels:
Output same as above
- Rows and columns can be selected ba their label, with the