How to use created variable in same assign function with pandas
You can use DataFrame.eval(..., inplace=False) method as follows:
In [79]: qry = """
...: z = x * y
...: w = z + 10 # NOTE: next variable must be on a new line
...: """
In [80]: df.eval(qry, inplace=False)
Out[80]:
x y z w
0 -0.636271 -0.493260 0.313847 10.313847
1 0.298998 0.266673 0.079735 10.079735
2 -0.836940 -0.593346 0.496595 10.496595
3 0.497099 -0.199589 -0.099215 9.900785
4 2.187165 -0.332140 -0.726445 9.273555
5 0.472785 0.169204 0.079997 10.079997
6 -0.847666 -1.519570 1.288088 11.288088
7 1.262524 1.008820 1.273660 11.273660
8 -0.632817 -0.463941 0.293590 10.293590
9 -0.955913 -1.149799 1.099107 11.099107
10 -1.260231 0.000266 -0.000336 9.999664
11 1.054885 -1.390762 -1.467094 8.532906
12 -1.048271 0.816762 -0.856187 9.143813
13 -0.814064 -0.070574 0.057452 10.057452
14 -1.279904 -1.079151 1.381211 11.381211
15 0.223787 -0.887732 -0.198663 9.801337
16 -0.493267 -0.064099 0.031618 10.031618
17 -0.549534 0.622976 -0.342346 9.657654
18 -0.261209 0.267250 -0.069808 9.930192
19 -2.948658 1.586422 -4.677815 5.322185
20 -1.959709 1.103462 -2.162465 7.837535
21 0.595782 -0.699891 -0.416983 9.583017
22 -0.059947 -0.264011 0.015827 10.015827
23 0.012929 -1.635020 -0.021139 9.978861
24 1.387415 -1.763467 -2.446660 7.553340
.. ... ... ... ...
75 1.649346 -0.515930 -0.850948 9.149052
76 -1.111928 -0.674379 0.749861 10.749861
77 1.413567 -1.377679 -1.947441 8.052559
78 0.119227 0.382638 0.045621 10.045621
79 0.064824 -2.043595 -0.132474 9.867526
80 -1.135878 -0.116922 0.132809 10.132809
81 -0.423820 1.386475 -0.587616 9.412384
82 0.642123 -0.914807 -0.587419 9.412581
83 -0.495118 0.773073 -0.382763 9.617237
84 0.347832 -0.913034 -0.317582 9.682418
85 1.314090 1.633140 2.146093 12.146093
86 -0.277789 0.883307 -0.245373 9.754627
87 0.514091 -1.349400 -0.693714 9.306286
88 -0.140958 -0.264500 0.037283 10.037283
89 -0.975843 -0.608312 0.593617 10.593617
90 0.242816 0.749860 0.182078 10.182078
91 1.185033 -0.487483 -0.577683 9.422317
92 -0.258952 -0.532178 0.137809 10.137809
93 2.015797 1.788613 3.605481 13.605481
94 -0.415403 0.224944 -0.093442 9.906558
95 -0.082239 -1.479761 0.121693 10.121693
96 -0.707825 2.074192 -1.468165 8.531835
97 0.517926 0.043832 0.022702 10.022702
98 -0.667368 -0.916520 0.611656 10.611656
99 0.366614 0.620221 0.227382 10.227382
[100 rows x 4 columns]
These are not equivalent. From the docs for assign (emphasis mine):
Assigning multiple columns within the same assign is possible, but you cannot reference other columns created within the same assign call.
This would be tricky to do in Python < 3.6 since the order of keyword arguments is not guaranteed. maxU's answer using a multi-line DataFrame.eval is a nice alternative approach to the problem.
There is also a GitHub issue
- API: allow dependent assignment? #14207
which notes that this behavior you want could be possible in Python 3.6 since kwarg argument order is preserved. It appears that the behavior may be adopted in pandas 2.0.