### Question :

Convert column to row in Python Pandas

I have the following Python pandas dataframe:

```
fruits | numFruits
---------------------
0 | apples | 10
1 | grapes | 20
2 | figs | 15
```

I want:

```
apples | grapes | figs
-----------------------------------------
Market 1 Order | 10 | 20 | 15
```

I have looked at pivot(), pivot_table(), Transpose and unstack() and none of them seem to give me this. Pandas newbie, so all help appreciated.

##
Answer #1:

You need `set_index`

with transpose by `T`

:

```
print (df.set_index('fruits').T)
fruits apples grapes figs
numFruits 10 20 15
```

If need rename columns, it is a bit complicated:

```
print (df.rename(columns={'numFruits':'Market 1 Order'})
.set_index('fruits')
.rename_axis(None).T)
apples grapes figs
Market 1 Order 10 20 15
```

Another faster solution is use `numpy.ndarray.reshape`

:

```
print (pd.DataFrame(df.numFruits.values.reshape(1,-1),
index=['Market 1 Order'],
columns=df.fruits.values))
apples grapes figs
Market 1 Order 10 20 15
```

**Timings**:

```
#[30000 rows x 2 columns]
df = pd.concat([df]*10000).reset_index(drop=True)
print (df)
In [55]: %timeit (pd.DataFrame([df.numFruits.values], ['Market 1 Order'], df.fruits.values))
1 loop, best of 3: 2.4 s per loop
In [56]: %timeit (pd.DataFrame(df.numFruits.values.reshape(1,-1), index=['Market 1 Order'], columns=df.fruits.values))
The slowest run took 5.64 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 424 µs per loop
In [57]: %timeit (df.rename(columns={'numFruits':'Market 1 Order'}).set_index('fruits').rename_axis(None).T)
100 loops, best of 3: 1.94 ms per loop
```

##
Answer #2:

```
pd.DataFrame([df.numFruits.values], ['Market 1 Order'], df.fruits.values)
apples grapes figs
Market 1 Order 10 20 15
```

*Refer to jezrael’s enhancement of this concept. df.numFruits.values.reshape(1, -1) is more efficient.*

##
Answer #3:

You can use transpose api of pandas as follow:

```
df.transpose()
```

Considering df as your pandas dataframe