To sort the rows in a dataframe in ascending order based on a column, taking into account the entire value of the number, you can use the sort_values() method of a pandas dataframe and set the parameter "key" to a lambda function that converts the columns to a numeric type. The code snippet below demonstrates how to do this:
import pandas as pd
# create a sample dataframe
data = {'name': ['Bob', 'Alice', 'John', 'Doe'],
'age': ['25', '22', '33', '18']}
df = pd.DataFrame(data)
# sort the dataframe in ascending order based on the 'age' column
df = df.sort_values('age', key=lambda x: pd.to_numeric(x, errors='coerce'))
print(df)
Output:
name age
3 Doe 18
1 Alice 22
0 Bob 25
2 John 33
Note: The errors='coerce' parameter in the pd.to_numeric() function is used to convert any non-numeric value to NaN (Not a Number) instead of throwing an error. This allows non-numeric values to be handled properly during sorting.
Asked: 2022-05-10 11:00:00 +0000
Seen: 8 times
Last updated: Jun 10 '21