如何使用 iloc [] select pandas dataframe 的倒数第二行 []？

Question

I fetch the data from online and store that data in a pandas dataframe. But the problem is the dataframe format is not same every time mainly numbers of rows.

Print(df.shape)
Output: (100, 9)

--

Print(df.shape)
Output: (33, 9)

--

Print(df.shape)
Output: (153, 9)

--

Print(df.shape)
Output: (148, 9)

Can you please tell me how we can select only second last row or second last row's any specific cell using iloc[]

Answer 1

df.iloc[-2] will get you the penultimate row info for all columns.

If you want a specific column only, df.loc doesn't like the minus sign, so one way you could do it would be: df.loc[(df.shape[0]-2), 'your_column_name']

Where df.shape[0] gets your row count, and -2 removes 2 from it to give you the index number for your penultimate row. Then you give it the required column name to only return that value.

Answer 2

You can get the second row from the back using index -2.

import pandas as pd
import numpy as np

a = np.matrix('1 2; 3 4; 5 6')
p = pd.DataFrame(a)
print("dataframe\n" + str(p))

print("second last row\n" + str(np.array(p.iloc[-2])))

Output:

dataframe
   0  1
0  1  2
1  3  4
2  5  6

second last row
[3 4]

Answer 3

You can also use take :

# all columns
df.take([-2])

# specific column
df['foo'].take([-2])