Python 基于 Pandas 数据框中的多列值选择行
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selecting rows based on multiple column values in pandas dataframe
提问by Ssank
I have a pandasDataFramedf:
我有一个pandasDataFramedf：
import pandas as pd
data = {"Name": ["AAAA", "BBBB"],
"C1": [25, 12],
"C2": [2, 1],
"C3": [1, 10]}
df = pd.DataFrame(data)
df.set_index("Name")
which looks like this when printed (for reference):
打印时看起来像这样（供参考）：
C1 C2 C3
Name
AAAA 25 2 1
BBBB 12 1 10
I would like to choose rows for which C1, C2and C3have values between 0and 20.
我想为 which 选择行C1，C2并且C3在0和之间具有值20。
Can you suggest an elegant way to select those rows?
你能建议一种优雅的方式来选择这些行吗？
采纳答案by kennes
I think below should do it, but its elegance is up for debate.
我认为下面应该这样做，但它的优雅有待商榷。
new_df = old_df[((old_df['C1'] > 0) & (old_df['C1'] < 20)) & ((old_df['C2'] > 0) & (old_df['C2'] < 20)) & ((old_df['C3'] > 0) & (old_df['C3'] < 20))]
回答by EdChum
Shorter version:
较短的版本：
In [65]:
df[(df>=0)&(df<=20)].dropna()
Out[65]:
Name C1 C2 C3
1 BBBB 12 1 10
回答by Rob Buckley
I like to use df.query() for these kind of things
我喜欢用 df.query() 做这些事情
df.query('C1>=0 and C1<=20 and C2>=0 and C2<=20 and C3>=0 and C3<=20')
回答by braham-snyder
df.query(
"0 < C1 < 20 and 0 < C2 < 20 and 0 < C3 < 20"
)
or
或者
df.query("0 < @df < 20").dropna()
Using @fooin df.queryrefers to the variable fooin the environment.
使用@fooindf.query是指foo环境中的变量。
