Pandas dataframe index by year

Question

I made a bunch of dataframes that are organized like this (lets call this df):

                   2014-12-31   2013-12-31  2012-12-31  2011-12-31
After Tax ROE     32             11          318        114
Cash Ratio        91             126          41        159
Current Ratio     152            188          97        195
Gross Margin      28             23           7         30
Operating Margin  6              3            95        123
Pre-Tax Margin    9              4            96        124
Pre-Tax ROE       31             11           318       113
Profit Margin     9              4            96        125
Quick Ratio       107            137          48        169

I wrote a script to scrape the NASDAQ site and make a bunch of these all for different stocks. I want to be able to compare these ratios for a year, for different stocks in this format:

2014
      AAPL GOOG TSLA 

ratio  int  int  int
ratio  int  int  int
ratio  int  int  int
ratio  int  int  int

I know I can just reference the columns like this df[[0]] to get the column out for 2014 for that particular dataframe.

But I want to index based on the year so it always works no matter how the columns are oriented. I made the column headings for df datetime objects specifically for that purpose. How do I do that?

Answer 1

You can have the columns as a DateTimeIndex which has more flexible selection.

For example:

import pandas as pd
import numpy as np

df = pd.DataFrame(
    np.arange(10).reshape((5, 2)),
    columns=pd.DatetimeIndex(['2014-04-14', '2015-05-15']))
print(df['2014'])