CODEWITHSUNDEEP
pythonpandas
user12907213
user12907213

Reputation:

Use row's values as columns

I would like to know how I can get something like this

Net     123  21   41   42  12  21
123      1   0    1    0    0   0
21       0   0    0    0    0   1
41       0   0    1    1    0   0
42       0   0    1    1    0   0
12       0   0    0    0    1   0
21       0   1    0    0    0   0

from the original dataset:

Net     L
123    [123,41]
21     [21]
41     [41,42]
42     [42,41]
12     [12]
21     [21]

I thought of explode, but it works only on rows, not on columns.

Upvotes: 1

Views: 71

Answers (2)

BENY
BENY

Reputation: 323276

We can do dot

s=df.drop('Net',1)
df['New']=s.dot(s.columns+',').str[:-1].str.split(',')
df
Out[283]: 
   Net  123  21  41  42  12    21        New
0  123    1   0   1   0   0     0  [123, 41]
1   21    0   0   0   0   0     1     [21.1]
2   41    0   0   1   1   0     0   [41, 42]
3   42    0   0   1   1   0     0   [41, 42]
4   12    0   0   0   0   1     0       [12]
5   21    0   1   0   0   0     0       [21]

Upvotes: 1

hoomant
hoomant

Reputation: 455

I assume the values in your column 'L' are str (not list), and each value is separated by a comma. If so, you can:

# create a set of column names
columns = set()
for cols in df.L.unique():
    cols = cols.split(',')
    for col in cols:
        columns.add(col)

# generate columns
for col in columns:
    df[col] = df.L.str.contains(col, regex=False)

# change False/True to 0/1
df.loc[:, columns] = df.loc[:, columns].astype(int)

Upvotes: 0

Related Questions