You can filter the rows of a DataFrame to only contain rows that meet some condition. For example, df[df.age >= 16]
would return a new DataFrame with same columns and only the rows for which the age value was greater than or equal to 16.
Using the DataFrame
import pandas as pd df = pd.DataFrame({'name': ['Jeff', 'Esha', 'Jia'], 'age': [30, 56, 8]})
name | age | |
---|---|---|
1 | Jeff | 30 |
2 | Esha | 56 |
3 | Jia | 8 |
Write a function, only_names_that_start_with_j(df)
which takes in the DataFrame and returns a new DataFrame with rows of names that start with 'J'.
Hint: the pandas .str
functions would be helpful here.
df = pd.DataFrame({'name': ['Jeff', 'Esha', 'Jia'], 'age': [30, 56, 8]})
name | age | |
---|---|---|
0 | Jeff | 30 |
1 | Esha | 56 |
2 | Jia | 8 |
name | age | |
---|---|---|
0 | Jeff | 30 |
2 | Jia | 8 |