根据条件从 Pandas DataFrame 中删除行 [英] Remove rows from pandas DataFrame based on condition
本文介绍了根据条件从 Pandas DataFrame 中删除行的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我是熊猫的新手,所以请原谅新手问题!
I am a newbie to pandas so please forgive the newbie question!
我有以下代码;
import pandas as pd
pet_names = ["Name","Species"
"Jack","Cat"
"Jill","Dog"
"Tom","Cat"
"Harry","Dog"
"Hannah","Dog"]
df = pd.DataFrame(pet_names)
df = df[df['Species']!='Cat']
print(df)
我想删除物种"列中包含猫"的所有行,留下所有的狗.我该怎么做呢?不幸的是,此代码目前正在返回错误.
I would like to remove all the rows that contain "Cat" in the "Species" column, leaving all the dogs behind. How do I do this? Unfortunately, this code is currently returning errors.
推荐答案
General boolean indexing
df[df['Species'] != 'Cat']
# df[df['Species'].ne('Cat')]
Index Name Species
1 1 Jill Dog
3 3 Harry Dog
4 4 Hannah Dog
df.query
df.query("Species != 'Cat'")
Index Name Species
1 1 Jill Dog
3 3 Harry Dog
4 4 Hannah Dog
有关 pd.eval()
函数系列、它们的特性和用例的信息,请访问 使用 pd.eval() 在 Pandas 中进行动态表达式评估.
For information on the pd.eval()
family of functions, their features and use cases, please visit Dynamic Expression Evaluation in pandas using pd.eval().
df[~df['Species'].isin(['Cat'])]
Index Name Species
1 1 Jill Dog
3 3 Harry Dog
4 4 Hannah Dog
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