How do I select columns a
and b
from df
, and save them into a new dataframe df1
?
index a b c
1 2 3 4
2 3 4 5
Unsuccessful attempt:
df1 = df['a':'b']
df1 = df.ix[:, 'a':'b']
dataframeindexingpandaspythonselect
How do I select columns a
and b
from df
, and save them into a new dataframe df1
?
index a b c
1 2 3 4
2 3 4 5
Unsuccessful attempt:
df1 = df['a':'b']
df1 = df.ix[:, 'a':'b']
Best Answer
The column names (which are strings) cannot be sliced in the manner you tried.
Here you have a couple of options. If you know from context which variables you want to slice out, you can just return a view of only those columns by passing a list into the
__getitem__
syntax (the []'s).Alternatively, if it matters to index them numerically and not by their name (say your code should automatically do this without knowing the names of the first two columns) then you can do this instead:
Additionally, you should familiarize yourself with the idea of a view into a Pandas object vs. a copy of that object. The first of the above methods will return a new copy in memory of the desired sub-object (the desired slices).
Sometimes, however, there are indexing conventions in Pandas that don't do this and instead give you a new variable that just refers to the same chunk of memory as the sub-object or slice in the original object. This will happen with the second way of indexing, so you can modify it with the
.copy()
method to get a regular copy. When this happens, changing what you think is the sliced object can sometimes alter the original object. Always good to be on the look out for this.To use
iloc
, you need to know the column positions (or indices). As the column positions may change, instead of hard-coding indices, you can useiloc
along withget_loc
function ofcolumns
method of dataframe object to obtain column indices.Now you can use this dictionary to access columns through names and using
iloc
.