CODEWITHSUNDEEP
pythonpython-2.7pandas
Sakura
Sakura

Reputation: 729

Modify multiple rows in dataframe

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?

Upvotes: 1

Views: 9523

Answers (2)

Abbas
Abbas

Reputation: 4070

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

Upvotes: 3

user2285236
user2285236

Reputation:

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

Upvotes: 6

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