Flag specific consecutive values in dataframe using python

Question

I have a dataframe with multiple columns. I need to flag 4th value to 8th value in Column2 indicating these consecutive rows have values equal to 0.1

ID           Column2      Column3
1              2.6            9
2              1.9            7
3              4.7            5
4              0.1            8     
5              0.1            6
6              0.1            2
7              0.1            8
8              0.1            7
9              3.0            4
10             1.2            9
11             2.8            7
12             3.1            9
13             1.0            3
14             2.4            4
15             3.2            5
n             nth value      nth value

I used following code and it gave me TypeError. Can anyone please help?

Code:

import pandas as pd
df = pd.read_csv('file.csv')

for row, index in df_May.iterrows():
    if row['Column2'] == row['Column2'].shift(1) | row['Column2'] == 0.1:
        print index,row

TypeError: 'int' object has no attribute '__getitem__'

how do you want to flag those rows? please post your desired data set — MaxU - stand with Ukraine
– MaxU - stand with Ukraine, Commented Jun 12, 2018 at 19:16

harpan · Accepted Answer · 2018-06-12 19:26:15Z

4

You need:

df.loc[(df['Column2'].diff()==0) | (df['Column2'].diff(-1)==0)]

Output:

    ID  Column2 Column3
3   4   0.1       8
4   5   0.1       6
5   6   0.1       2
6   7   0.1       8
7   8   0.1       7

edited Jun 12, 2018 at 19:26

answered Jun 12, 2018 at 19:19

harpan

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2 Comments

ALollz Over a year ago

I think add or .diff(-1) == 0 to also catch the first occurrence.

user9264558 Over a year ago

@HarvIpan that worked like magic! Thanks for making it so simple. ALollz, thanks for your comment.

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