如何在 pandas 中使用 r 的 seq function

Question

i want of sequence of values to be written on new column based on previous columns

this is my dataframe df

a  b
11 15
32 35

i want output to be like this

a  b   c
11 15  11,12,13,14
32 35  32,33,34

it should get sequence from first two columns

my code

df.apply(lambda x : range(x['a'],x['b']),1)

it gives me some thing like this not able to remove paranthesis and split by comma into multiple rows

a  b   c
11 15  (11,12,13,14)
32 35  (32,33,34)

Answer 1

Since you mentioned you want to convert the values into rows you can do it from the generated tuple using explode . Otherwise @jezrael answer should work fine for you.

df = pd.DataFrame([[11, 15],[32, 35]],columns=['a','b'])
df['c']= df.apply(lambda x : range(x['a'],x['b']),1)

df.explode('c')

Out:

    a   b   c
0  11  15  11
0  11  15  12
0  11  15  13
0  11  15  14
1  32  35  32
1  32  35  33
1  32  35  34

Answer 2

You can convert values to strings and join by join :

df['c'] = df.apply(lambda x : ','.join(str(i) for i in range(x['a'],x['b'])),1)
#alternative
#df['c'] = [','.join(str(i) for i in range(x,y)) for x, y in df[['a','b']].to_numpy()]

Or:

df['c'] = df.apply(lambda x : ','.join(map(str, range(x['a'],x['b']))),1)
#alternative
#df['c'] = [','.join(map(str, range(x,y))) for x, y in df[['a','b']].to_numpy()]

---

print (df)
    a   b            c
0  11  15  11,12,13,14
1  32  35     32,33,34

EDIT: For new rows use DataFrame.explode :

df['c']= df.apply(lambda x : range(x['a'],x['b']),1)

df = df.explode('c').reset_index(drop=True)

print (df)
    a   b   c
0  11  15  11
1  11  15  12
2  11  15  13
3  11  15  14
4  32  35  32
5  32  35  33
6  32  35  34