Assume, you have a dataframe and the result for second lowest value in each column as,
Id 2 Salary 30000 Age 23
To solve this, we will follow the steps given below −
Solution
Define a dataframe
Set df.apply() function inside create lambda function and set the variable like x to access all columns and check expression as
x.sort_values().unique()[1] with axis=0 to return second lowest value as,
result = df.apply(lambda x: x.sort_values().unique()[1], axis=0)
Example
Let’s check the following code to get a better understanding −
import pandas as pd
df = pd.DataFrame({'Id':[1,2,3,4,5,6,7,8,9,10],
'Salary':[20000,30000,50000,40000,80000,90000,350000,55000,60000,70000],
'Age': [22,23,24,25,26,25,26,27,25,24]
})
print("DataFrame is:\n",df)
print("Second lowest value of each column is:")
result = df.apply(lambda x: x.sort_values().unique()[1], axis=0)
print(result)Output
DataFrame is: Id Salary Age 0 1 20000 22 1 2 30000 23 2 3 50000 24 3 4 40000 25 4 5 80000 26 5 6 90000 25 6 7 350000 26 7 8 55000 27 8 9 60000 25 9 10 70000 24 Second lowest value of each column is: Id 2 Salary 30000 Age 23 dtype: int64