python - 当值大于某个值时如何返回第一个索引

Question

这是为了模拟结构化投资中的“淘汰”情况。一般分为三只股票:股票A；库存B；股票C，每月观察其价格是否高于第一个月价格(KO水平)的100%。

基本数据框如下所示:

           Stock-A Stock-B Stock-C
2010-01-01   10      20       40
2010-02-01   9.5     18       31
2010-03-01   10.5    22       39
2010-04-01   11.5    23       36

如果其中一个价格高于 KO 水平，该函数应返回月份并且不再需要监控价格。

例如，股票 A 在 2010-03-01 跨越 KO 级别，因此该函数应将其标记为成功的“淘汰”股票并返回日期，即 2010-03-01 .

如果有一只股票永远不会越界，该函数应该遍历结束并将其作为未淘汰的股票返回。我怎样才能做到这一点？

Answer 1

这是我的尝试，有一些假设(另外，对此持保留态度:我并没有声称自己是 Pandas 专家，只是认为这将是一个值得研究的有趣问题)

df = pandas.DataFrame([
    {'date': '2010-01-01', 'stock_a': 10, 'stock_b': 20, 'stock_c': 30},
    {'date': '2010-01-02', 'stock_a': 9.5, 'stock_b': 18, 'stock_c': 31},
    {'date': '2010-03-01', 'stock_a': 10.5, 'stock_b': 22, 'stock_c': 39},
    {'date': '2010-04-01', 'stock_a': 11.5, 'stock_b': 23, 'stock_c': 36},
])
# Assuming you want the first chronological record of such an event
df = df.sort_values(['date', 'stock_a', 'stock_b', 'stock_c'])
df2 = pandas.concat([
    df['stock_a'] > df['stock_a'][0],
    df['stock_b'] > df['stock_b'][0],
    df['stock_c'] > df['stock_c'][0],
], axis=1)
df2['date'] = True
# At this point columns stock_{a,b,c} are populated with NaN in place where the value
# was less than the first observation
df3 = df[df2].query('stock_a == stock_a & stock_b == stock_b & stock_c == stock_c')

if not df3.empty:
    print df3.iloc[[0]]
print 'No match'