concatenating a dataframe row values into one with consistent padding

user_11585258 0
Viewed 71

I've a dataframe like below

+---+----+---+----+----+-----+------+
| X | XX | Y | YY | ZZ | ZZZ | ZZZZ |
+---+----+---+----+----+-----+------+
| 0 |  1 | 1 |  0 |  0 |  1  |   0  |
+---+----+---+----+----+-----+------+
| 1 |  0 | 0 |  1 |  0 |  0  |   1  |
+---+----+---+----+----+-----+------+
| 0 |  1 | 0 |  0 |  1 |  0  |   0  |
+---+----+---+----+----+-----+------+
| 0 |  0 | 1 |  0 |  0 |  0  |   0  |
+---+----+---+----+----+-----+------+

df = pd.DataFrame({
    'X':[0,1,0,0],
    'XX':[1,0,1,0],
    'Y':[1,0,0,1],
    'YY':[0,1,0,0],
    'ZZ':[0,0,1,0],
    'ZZZ':[1,0,0,0],
    'ZZZZ':[0,1,0,0]
})

I want to concatenate the dataframe row values into one with consistent padding.

I tried the below code

df.dot(df.columns +' | ')

| sign with extra spaces before and after.

what I get is

0     XX | Y | ZZZ |
1    X | YY | ZZZZ |
2          XX | ZZ |
3                Y |
dtype: object

But, what I expect to receive is

0      XX |  Y |  ZZZ |
1       X | YY | ZZZZ |
2           XX |   ZZ |
3                   Y |
        dtype: object

notice the alignment in | sign.

How can I modify my code to add this extra variable padding spaces? pandas or numpy solution preferred.

pandas numpy python
2 Answers

One idea is add space for constant padding by maximal length of string in columns names:

print (df.columns.str.len().max())
4

df = df.dot(df.columns.str.rjust(df.columns.str.len().max(), ' ') +' | ')
#working like
#df = df.dot(df.columns.str.rjust(4, ' ') +' | ')
print (df)
0      XX |    Y |  ZZZ | 
1       X |   YY | ZZZZ | 
2             XX |   ZZ | 
3                     Y | 
dtype: object
user_29010020 
g=df.gt(0).columns*df
g.agg(set,1).map(list).str.join('|').str.strip('\w')
user_89869750
Related