[英]Vectorized operation on three columns
首先,讓我們創建隨機 dataframe:
df = pd.DataFrame(
{
"A": np.random.randint(0, 70, size=5),
"B": np.random.randint(-10, 35, size=5),
"C": np.random.randint(10, 50, size=5)
}
)
然后,我使用min和max函數來創建兩個額外的列:
df['max'] = df[['A', 'B', 'C']].max(axis=1)
df['min'] = df[['A', 'B', 'C']].min(axis=1)
Output:
A B C max min
0 17 26 31 31 17
1 45 31 17 45 17
2 36 24 31 36 24
3 16 17 24 24 16
4 16 12 23 23 12
什么是最有效和最優雅的方式來獲得“中間”列的剩余價值,以便 output 看起來像這樣:
A B C max min mid
0 17 26 31 31 17 26
1 45 31 17 45 17 31
2 36 24 31 36 24 31
3 16 17 24 24 16 17
4 16 12 23 23 12 16
我正在尋找矢量化解決方案。 我能夠使用條件來實現這一點:
conditions = [((df['A'] > df['B']) & (df['A'] < df['C']) | (df['A'] > df['C']) & (df['A'] < df['B'])),
((df['B'] > df['A']) & (df['B'] < df['C']) | (df['B'] > df['C']) & (df['B'] < df['A'])),
((df['C'] > df['A']) & (df['C'] < df['B']) | (df['C'] > df['B']) & (df['C'] < df['A']))]
choices = [df['A'], df['B'], df['C']]
df['mid'] = np.select(conditions, choices, default=0)
但是,我認為有更優雅的解決方案。
你應該使用median
嗎?
df[["A","B","C"]].median(axis=1)
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