根据数据框 pandas 中行的条件删除特定行

Question

我想根据 Pandas 数据框中行的条件删除特定行。

例如，由于我同时有几个货币对，我打算只选择同一时间的一种货币。

这是优先级：欧元、美元、英镑、瑞士法郎。

currency    timebuy buyprice
CNHUSD  2021-01-05 08:30:00 0,00005073
CNHGBP  2021-01-05 08:30:00 1,588
ZARGBP  2021-01-07 05:15:00 0,2727
ZARUSD  2021-01-07 05:15:00 300
ZAREUR  2021-01-07 13:00:00 0,1936
ZARCHF  2021-01-07 13:00:00 0,0000052
JPYCHF  2021-01-13 06:00:00 0,0002222
JPYUSD  2021-01-13 06:00:00 8
JPYGBP  2021-01-13 06:00:00 8

Answer 1

对于这样的优先级列表，使用数字是最容易的。 因此，您可以从优先级列表中创建一个不错的数字映射，并使用它来选择行：

priority = ['EUR', 'USD', 'GBP', 'CHF']
mapping = {p: i for i, p in enumerate(priority)}
indexes = df['currency'].str[-3:].map(mapping).groupby(df['currency'].str[:3]).idxmin().sort_values()
selected = df.loc[indexes]

输出：

>>> selected
  currency             timebuy    buyprice
0   CNHUSD 2021-01-05 08:30:00  0,00005073
4   ZAREUR 2021-01-07 13:00:00      0,1936
7   JPYUSD 2021-01-13 06:00:00           8

单线：

priority = ['EUR', 'USD', 'GBP', 'CHF']
filtered = df.loc[df['currency'].str[-3:].map({p: i for i, p in enumerate(priority)}).groupby(df['currency'].str[:3]).idxmin().sort_values()]

如果您想按每个时间戳而不是前 3 个字母进行分组currency ，请按df['timestamp']而不是df['currency'].str[:3]分组，即：

indexes = df['currency'].str[-3:].map(mapping).groupby(df['timestamp']).idxmin().sort_values()
                                                     # ^^^^^^^^^^^^^^^   

Answer 2

有点笨拙的方法：

# Hard-code your priority for the second currency in each pair
pri = ['EUR', 'USD', 'GBP', 'CHF']

# Create a new column for the second currency of each pair
df['2ndcurr'] = df['currency'].str[-3:]


# Group by time and second currency,
# Sort inner level (1) of resulting MultiIndex to match priority,
# Group by the outer level (0),
# Get the first row of each group,
# Reset timebuy from index into its own column

(df.set_index(['timebuy', '2ndcurr'])
   .reindex(pri, level=1)
   .groupby(level=0)
   .first()
   .reset_index())

               timebuy currency    buyprice
0  2021-01-05 08:30:00   CNHUSD  0,00005073
1  2021-01-07 05:15:00   ZARUSD         300
2  2021-01-07 13:00:00   ZAREUR      0,1936
3  2021-01-13 06:00:00   JPYUSD           8