Adding a new column to DataFrame with different values in different row

Question

I have a DataFrame df which has 50 columns in it and it has 28800 rows. I want to add a new column col_new which will have value 0 in every rows from 2880 to 5760 ,12960 to 15840 and 23040 to 25920. And all other rows will have value 1.

How could I do that?

score 1 · Accepted Answer · answered Nov 27 '21 at 23:17

1

Believe what you are looking for is actually answered here: Add column in dataframe from list

myList = [1,2,3,4,5]
print(len(df)) # 50
df['new_col'] = mylist
print(len(df)) # 51

Alternatively, you could set the value of a slice of the list like so:

data['new_col'] = 1
data.loc[2880:5760, 'new_col'] = 0
data.loc[12960:15840, 'new_col'] = 0
data.loc[23040:25920, 'new_col'] = 0

answered Nov 27 '21 at 23:17

bguest

197
6

if index starts in 0, that would change from row 2881th instead of 2880th, if index starts in one that would be ok. – jwzinserl Nov 27 '21 at 23:27
I'm sure OP can figure this out – bguest Dec 01 '21 at 13:00

jwzinserl · Answer 2 · 2021-11-27T23:18:14.770

0

df = pd.DataFrame([i for i in range(28800)])
df["new_col"] = 1
zeros_bool = [(
    (i>=(2880-1) and i<5760) or (i>=(12960-1) and i<15840) or (i>=(23040-1) and i<25920)
) for i in range(28800)]
df.loc[zeros_bool,"new_col"] = 0

edited Nov 27 '21 at 23:18

answered Nov 27 '21 at 23:11

jwzinserl

347
1
2
7

Adding a new column to DataFrame with different values in different row

2 Answers2