Modify multiple rows in dataframe

Question

assume I have a dataframe. I would like to modify a list of rows with certain value.

For example, below is my dataframe.

df = pd.DataFrame({
"strings":["A", "B", "C", "D", "E"], 
  "value":["a", "b", "c", "d", "f"], 
  "price":["1", "2", "3", "4", "5"]})

And I want to replace all cells with '0' in row C, D, and E, which is like below. Rows = ['C', 'D', 'E']

df = pd.DataFrame({
"strings":["A", "B", "C", "D", "E"], 
  "value":["a", "b", "0", "0", "0"], 
  "price":["1", "2", "0", "0", "0"]})

I know we can achieve this by simply giving the rows' name and certain value, but as we have lots of rows to be modified, how could we do this more efficiently using pandas?

Anyone hint please?

Do you mean COLUMN C, D, E? C, D and E are not rows

dahui
– dahui

2016-05-03 15:16:03 +00:00
Commented May 3, 2016 at 15:16 — dahui
– dahui, Commented May 3, 2016 at 15:16
@dahui C, D, E are not Columns either

Joe T. Boka
– Joe T. Boka

2016-05-03 15:17:48 +00:00
Commented May 3, 2016 at 15:17 — Joe T. Boka
– Joe T. Boka, Commented May 3, 2016 at 15:17

user2285236 · Accepted Answer · 2016-05-03 15:21:37Z

6

If I understood correctly, you want all the values in columns "price" and "value" to be set to zero for rows where column "strings" has values either C, D or E.

df.loc[df.strings.isin(["C", "D", "E"]), df.columns.difference(["strings"])] = 0
df
Out[82]: 
  price strings value
0     1       A     a
1     2       B     b
2     0       C     0
3     0       D     0
4     0       E     0

answered May 3, 2016 at 15:21

user2285236

Sign up to request clarification or add additional context in comments.

6 Comments

IanS Over a year ago

difference is better :)

Sakura Over a year ago

Thanks, but if I have hundreds of rows required to be modified, what should I do??

user2285236 Over a year ago

@Sakura How do you identify the rows that should be modified? Are they in a list or something like that? Do they follow a rule?

Sakura Over a year ago

That is a list of them, no particular rule.

user2285236 Over a year ago

@Sakura then you can just pass the name of the list. For example df.loc[df.strings.isin(name_of_the_list), df.columns.difference(["strings"])] = 0

|

Abbas · Accepted Answer · 2021-02-09 11:39:31Z

3

Here is another way of doing it,

Consider your data is like this:

  price strings value
0     1       A     a
1     2       B     b
2     3       C     c
3     4       D     d
4     5       E     f

Now lets make strings column as the index:

df.set_index('strings', inplace=True)

#Result
        price value
strings
A           1     a
B           2     b
C           3     c
D           4     d
E           5     f

Now set the values of rows C, D, E as 0

df.loc[['C', 'D','E']] = 0

#Result
        price value
strings
A           1     a
B           2     b
C           0     0
D           0     0
E           0     0

edited Feb 9, 2021 at 11:39

answered May 3, 2016 at 15:24

Abbas

4,0897 gold badges45 silver badges66 bronze badges

Collectives™ on Stack Overflow

Modify multiple rows in dataframe

2 Answers 2

6 Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

6 Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related