I have a dataframe:
>>> dt
COL000 COL001 QT
STK_ID RPT_Date
STK000 20120331 2.6151 2.1467 1
20120630 4.0589 2.3442 2
20120930 4.4547 3.9204 3
20121231 4.1360 3.8559 4
STK001 20120331 -0.2178 0.9184 1
20120630 -1.9639 0.7900 2
20120930 -2.9147 1.0189 3
20121231 -2.5648 2.3743 4
STK002 20120331 -0.6426 0.9543 1
20120630 -0.3575 1.6085 2
20120930 -2.3549 0.7174 3
20121231 -3.4860 1.6324 4
And I want the columns values divided by 'QT' column, somewhat like this:
dt = dt/dt.QT # pandas does not accept this syntax
The desired output is:
STK_ID RPT_Date COL000 COL001 QT
STK000 20120331 2.615110188 2.146655745 1
20120630 2.029447265 1.172093561 1
20120930 1.484909881 1.306795608 1
20121231 1.034008443 0.963970609 1
STK001 20120331 -0.217808111 0.918355842 1
20120630 -0.981974837 0.394977675 1
20120930 -0.97157148 0.339633733 1
20121231 -0.641203355 0.593569537 1
STK002 20120331 -0.642567516 0.954323016 1
20120630 -0.178759288 0.804230898 1
20120930 -0.784982521 0.239117442 1
20121231 -0.871501505 0.408094317 1
How to do that?
The / operator for dv seems equal to div with default axis "columns". Set the axis to "index", then it'll work.
df = df.div(df.QT, axis='index')
Another tricky way is to transpose it first, divide it, and then transpose back:
df = (df.T / df.QT).T
来源：https://stackoverflow.com/questions/15916612/how-to-divide-the-value-of-pandas-columns-by-the-other-column