Remove rows from pandas DataFrame based on condition

Question

I am a newbie to pandas so please forgive the newbie question!

I have the following code;

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)

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.

Solution

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

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.isin

df[~df['Species'].isin(['Cat'])]

  Index    Name Species
1     1    Jill     Dog
3     3   Harry     Dog
4     4  Hannah     Dog