How to write the value in a column for specific rows?
0
I have a excel file, i need to write the specific value in a set of specific row:
For Ex: i have 20 rows and 5 columns
i need to add new column, and write the new column value(as x in first 5 rows, next 5 values (y) in next 5 rows and so on).
may i know how to achieve it?
col1 col2 col3 col4
1 a1 b1 c1
2 a2 * *
3 a3 * *
4 a4 * *
5 a5 * *
6 a6 * *
7 a7 * *
8 a8 * *
9 a9 * *
10 a10 * *
11 a11 * *
12 a12 * *
13 a13 * *
14 a14 * *
15 a15 * *
16 a16 * c16
17 a17 * c17
18 a18 * c18
19 a19 * c19
I need output like this:
col1 col2 col3 col4 colnew
1 a1 b1 c1 aa
2 a2 * * aa
3 a3 * * aa
4 a4 * * aa
5 a5 * * aa
6 a6 * * bb
7 a7 * * bb
8 a8 * * bb
9 a9 * * bb
10 a10 * * bb
11 a11 * * cc
12 a12 * * cc
13 a13 * * cc
14 a14 * * cc
15 a15 * * cc
16 a16 * c16 dd
17 a17 * c17 dd
18 a18 * c18 dd
19 a19 * c19 dd
python excel pandas
edited Nov 20 at 7:34
pygo
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
add a comment |
0
I have a excel file, i need to write the specific value in a set of specific row:
For Ex: i have 20 rows and 5 columns
i need to add new column, and write the new column value(as x in first 5 rows, next 5 values (y) in next 5 rows and so on).
may i know how to achieve it?
col1 col2 col3 col4
1 a1 b1 c1
2 a2 * *
3 a3 * *
4 a4 * *
5 a5 * *
6 a6 * *
7 a7 * *
8 a8 * *
9 a9 * *
10 a10 * *
11 a11 * *
12 a12 * *
13 a13 * *
14 a14 * *
15 a15 * *
16 a16 * c16
17 a17 * c17
18 a18 * c18
19 a19 * c19
I need output like this:
col1 col2 col3 col4 colnew
1 a1 b1 c1 aa
2 a2 * * aa
3 a3 * * aa
4 a4 * * aa
5 a5 * * aa
6 a6 * * bb
7 a7 * * bb
8 a8 * * bb
9 a9 * * bb
10 a10 * * bb
11 a11 * * cc
12 a12 * * cc
13 a13 * * cc
14 a14 * * cc
15 a15 * * cc
16 a16 * c16 dd
17 a17 * c17 dd
18 a18 * c18 dd
19 a19 * c19 dd
python excel pandas
edited Nov 20 at 7:34
pygo
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26
add a comment |
0
0
0
I have a excel file, i need to write the specific value in a set of specific row:
For Ex: i have 20 rows and 5 columns
i need to add new column, and write the new column value(as x in first 5 rows, next 5 values (y) in next 5 rows and so on).
may i know how to achieve it?
col1 col2 col3 col4
1 a1 b1 c1
2 a2 * *
3 a3 * *
4 a4 * *
5 a5 * *
6 a6 * *
7 a7 * *
8 a8 * *
9 a9 * *
10 a10 * *
11 a11 * *
12 a12 * *
13 a13 * *
14 a14 * *
15 a15 * *
16 a16 * c16
17 a17 * c17
18 a18 * c18
19 a19 * c19
I need output like this:
col1 col2 col3 col4 colnew
1 a1 b1 c1 aa
2 a2 * * aa
3 a3 * * aa
4 a4 * * aa
5 a5 * * aa
6 a6 * * bb
7 a7 * * bb
8 a8 * * bb
9 a9 * * bb
10 a10 * * bb
11 a11 * * cc
12 a12 * * cc
13 a13 * * cc
14 a14 * * cc
15 a15 * * cc
16 a16 * c16 dd
17 a17 * c17 dd
18 a18 * c18 dd
19 a19 * c19 dd
python excel pandas
edited Nov 20 at 7:34
pygo
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
I have a excel file, i need to write the specific value in a set of specific row:
For Ex: i have 20 rows and 5 columns
i need to add new column, and write the new column value(as x in first 5 rows, next 5 values (y) in next 5 rows and so on).
may i know how to achieve it?
col1 col2 col3 col4
1 a1 b1 c1
2 a2 * *
3 a3 * *
4 a4 * *
5 a5 * *
6 a6 * *
7 a7 * *
8 a8 * *
9 a9 * *
10 a10 * *
11 a11 * *
12 a12 * *
13 a13 * *
14 a14 * *
15 a15 * *
16 a16 * c16
17 a17 * c17
18 a18 * c18
19 a19 * c19
I need output like this:
col1 col2 col3 col4 colnew
1 a1 b1 c1 aa
2 a2 * * aa
3 a3 * * aa
4 a4 * * aa
5 a5 * * aa
6 a6 * * bb
7 a7 * * bb
8 a8 * * bb
9 a9 * * bb
10 a10 * * bb
11 a11 * * cc
12 a12 * * cc
13 a13 * * cc
14 a14 * * cc
15 a15 * * cc
16 a16 * c16 dd
17 a17 * c17 dd
18 a18 * c18 dd
19 a19 * c19 dd
python excel pandas
python excel pandas
edited Nov 20 at 7:34
pygo
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
edited Nov 20 at 7:34
pygo
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
edited Nov 20 at 7:34
pygo
1,8521516
edited Nov 20 at 7:34
pygo
1,8521516
edited Nov 20 at 7:34
pygo
1,8521516
1,8521516
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
asked Nov 20 at 7:22
Sanakiyan Sundarrajan S
6
6
please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26
add a comment |
please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26
please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26
please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26
add a comment |
1 Answer
1
active
oldest
votes
1
Use floor division by 5 first and then map by dictionary - if some value is missing in dict get NaNs in output column:
vals = ['aa','bb','cc','dd','ee']
d = dict(enumerate(vals))
print (d)
{0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd', 4: 'ee'}
#default range index
df['new'] = (df.index // 5).map(d.get)
#general solution
#df['new'] = pd.Series(np.arange(len(df)) // 5, index=df.index).map(d)
print (df)
col1 col2 col3 col4 new
0 1 a1 b1 c1 aa
1 2 a2 * * aa
2 3 a3 * * aa
3 4 a4 * * aa
4 5 a5 * * aa
5 6 a6 * * bb
6 7 a7 * * bb
7 8 a8 * * bb
8 9 a9 * * bb
9 10 a10 * * bb
10 11 a11 * * cc
11 12 a12 * * cc
12 13 a13 * * cc
13 14 a14 * * cc
14 15 a15 * * cc
15 16 a16 * c16 dd
16 17 a17 * c17 dd
17 18 a18 * c18 dd
18 19 a19 * c19 dd
answered Nov 20 at 7:28
jezrael
318k22257336
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
Use floor division by 5 first and then map by dictionary - if some value is missing in dict get NaNs in output column:
vals = ['aa','bb','cc','dd','ee']
d = dict(enumerate(vals))
print (d)
{0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd', 4: 'ee'}
#default range index
df['new'] = (df.index // 5).map(d.get)
#general solution
#df['new'] = pd.Series(np.arange(len(df)) // 5, index=df.index).map(d)
print (df)
col1 col2 col3 col4 new
0 1 a1 b1 c1 aa
1 2 a2 * * aa
2 3 a3 * * aa
3 4 a4 * * aa
4 5 a5 * * aa
5 6 a6 * * bb
6 7 a7 * * bb
7 8 a8 * * bb
8 9 a9 * * bb
9 10 a10 * * bb
10 11 a11 * * cc
11 12 a12 * * cc
12 13 a13 * * cc
13 14 a14 * * cc
14 15 a15 * * cc
15 16 a16 * c16 dd
16 17 a17 * c17 dd
17 18 a18 * c18 dd
18 19 a19 * c19 dd
answered Nov 20 at 7:28
jezrael
318k22257336
add a comment |
1
Use floor division by 5 first and then map by dictionary - if some value is missing in dict get NaNs in output column:
vals = ['aa','bb','cc','dd','ee']
d = dict(enumerate(vals))
print (d)
{0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd', 4: 'ee'}
#default range index
df['new'] = (df.index // 5).map(d.get)
#general solution
#df['new'] = pd.Series(np.arange(len(df)) // 5, index=df.index).map(d)
print (df)
col1 col2 col3 col4 new
0 1 a1 b1 c1 aa
1 2 a2 * * aa
2 3 a3 * * aa
3 4 a4 * * aa
4 5 a5 * * aa
5 6 a6 * * bb
6 7 a7 * * bb
7 8 a8 * * bb
8 9 a9 * * bb
9 10 a10 * * bb
10 11 a11 * * cc
11 12 a12 * * cc
12 13 a13 * * cc
13 14 a14 * * cc
14 15 a15 * * cc
15 16 a16 * c16 dd
16 17 a17 * c17 dd
17 18 a18 * c18 dd
18 19 a19 * c19 dd
answered Nov 20 at 7:28
jezrael
318k22257336
add a comment |
1
1
1
Use floor division by 5 first and then map by dictionary - if some value is missing in dict get NaNs in output column:
vals = ['aa','bb','cc','dd','ee']
d = dict(enumerate(vals))
print (d)
{0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd', 4: 'ee'}
#default range index
df['new'] = (df.index // 5).map(d.get)
#general solution
#df['new'] = pd.Series(np.arange(len(df)) // 5, index=df.index).map(d)
print (df)
col1 col2 col3 col4 new
0 1 a1 b1 c1 aa
1 2 a2 * * aa
2 3 a3 * * aa
3 4 a4 * * aa
4 5 a5 * * aa
5 6 a6 * * bb
6 7 a7 * * bb
7 8 a8 * * bb
8 9 a9 * * bb
9 10 a10 * * bb
10 11 a11 * * cc
11 12 a12 * * cc
12 13 a13 * * cc
13 14 a14 * * cc
14 15 a15 * * cc
15 16 a16 * c16 dd
16 17 a17 * c17 dd
17 18 a18 * c18 dd
18 19 a19 * c19 dd
answered Nov 20 at 7:28
jezrael
318k22257336
Use floor division by 5 first and then map by dictionary - if some value is missing in dict get NaNs in output column:
vals = ['aa','bb','cc','dd','ee']
d = dict(enumerate(vals))
print (d)
{0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd', 4: 'ee'}
#default range index
df['new'] = (df.index // 5).map(d.get)
#general solution
#df['new'] = pd.Series(np.arange(len(df)) // 5, index=df.index).map(d)
print (df)
col1 col2 col3 col4 new
0 1 a1 b1 c1 aa
1 2 a2 * * aa
2 3 a3 * * aa
3 4 a4 * * aa
4 5 a5 * * aa
5 6 a6 * * bb
6 7 a7 * * bb
7 8 a8 * * bb
8 9 a9 * * bb
9 10 a10 * * bb
10 11 a11 * * cc
11 12 a12 * * cc
12 13 a13 * * cc
13 14 a14 * * cc
14 15 a15 * * cc
15 16 a16 * c16 dd
16 17 a17 * c17 dd
17 18 a18 * c18 dd
18 19 a19 * c19 dd
answered Nov 20 at 7:28
jezrael
318k22257336
edited Nov 20 at 7:34
answered Nov 20 at 7:28
jezrael
318k22257336
answered Nov 20 at 7:28
jezrael
318k22257336
answered Nov 20 at 7:28
jezrael
318k22257336
318k22257336
add a comment |
add a comment |
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please read this before you post: stackoverflow.com/help/how-to-ask
– Zanshin
Nov 20 at 7:26