Divide DataFrame by first row

Question

I have checked the documentation. I don't understand the way to index a Pandas DataFrame.

I would like to divide a DataFrame of stock prices by their respective initial values to index the different stocks to 100. I want to compare their performance. The DataFrame looks like this:

>>> IndexPrices
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 157 entries, 1999-12-31 00:00:00 to 2012-12-31 00:00:00
Freq: M
Data columns:
MSCI WORLD :G U$                        148  non-null values
S&P 500 COMPOSITE                       148  non-null values
DAX 30 PERFORMANCE                      148  non-null values
RUSSELL 2000                            148  non-null values
FTSE 100                                148  non-null values
US Treasury Bond Yields 30 Year Bond    148  non-null values
dtypes: float64(6)

I have stuff like this, but it's not getting me anywhere.

IndexPrices.divide(IndexPrices[0:1])

Answer 1

In [193]: df
Out[193]:
   A  B  C  D
a  1  8  9  1
b  5  4  3  6
c  4  6  1  3
d  1  0  2  9

In [194]: df.divide(df.ix[0] / 100)
Out[194]:
     A    B           C    D
a  100  100  100.000000  100
b  500   50   33.333333  600
c  400   75   11.111111  300
d  100    0   22.222222  900