conversion column names into first row

Question

I would like to convert the following dataframe into a json .

df:
                               A   sector    B     sector    C     sector                              
TTM Ratio                      --   35.99   12.70  20.63  14.75      23.06
RRM Sales                      --  114.57    1.51   5.02   1.00    4594.13
MQR book                     1.48    2.64    1.02   2.46   2.73       2.74
TTR cash                       --   14.33    7.41  15.35   8.59  513854.86

In order to do so by using the function df.to_json() I would need to have unique names in column and indices.

Therefore what I am looking for is to convert the column names into a row and have default column numbers . In short I would like the following output:

df:
                               0     1       2       3       4       5 
                               A   sector    B     sector    C     sector                              
TTM Ratio                      --   35.99   12.70  20.63  14.75      23.06
RRM Sales                      --  114.57    1.51   5.02   1.00    4594.13
MQR book                     1.48    2.64    1.02   2.46   2.73       2.74
TTR cash                       --   14.33    7.41  15.35   8.59  513854.86

Turning the column names into the first row so I can make the conversion correctly .

Answer 1

You could also use vstack in numpy:

>>> df
   x  y  z
0  8  7  6
1  6  5  4

>>> pd.DataFrame(np.vstack([df.columns, df]))
   0  1  2
0  x  y  z
1  8  7  6
2  6  5  4

The columns become the actual first row in this case.

Answer 2

Use assign by list of range and original column names:

print (range(len(df.columns)))
range(0, 6)

#for python2 list can be omit
df.columns = [list(range(len(df.columns))), df.columns]

Or MultiIndex.from_arrays:

df.columns = pd.MultiIndex.from_arrays([range(len(df.columns)), df.columns])

---

Also is possible use RangeIndex:

print (pd.RangeIndex(len(df.columns)))
RangeIndex(start=0, stop=6, step=1)

df.columns = pd.MultiIndex.from_arrays([pd.RangeIndex(len(df.columns)), df.columns])
print (df)
              0       1      2        3      4          5
              A  sector      B   sector      C     sector
TTM Ratio    --   35.99  12.70    20.63  14.75      23.06
RRM Sales    --  114.57   1.51     5.02   1.00    4594.13
MQR book   1.48    2.64   1.02     2.46   2.73       2.74
TTR cash     --   14.33   7.41    15.35   8.59  513854.86