Joining two columns in the same data frame

Question

I am trying to add one column at the end of another column. I have included a picture that kind of demonstrates what I want to achieve. How can this be done?

For example, in this case I added the age column under the name column

enter image description here

Dummy data:

{'Unnamed: 0': {0: nan, 1: nan, 2: nan, 3: nan},
 'age ': {0: 35, 1: 56, 2: 22, 3: 16},
 'name': {0: 'andrea', 1: 'juan', 2: 'jose ', 3: 'manuel'},
 'sex': {0: 'female', 1: 'male ', 2: 'male ', 3: 'male '}}

@Chris I cannot post the data itself as it is classified. Sorry about that — paytonM, Jul 21 '20 at 18:07
Do you want age data column to put it under the name column data? — Jimmys, Jul 21 '20 at 18:08
@Jimmys well the issue is that I don;t really know how to achieve it — paytonM, Jul 21 '20 at 18:09
@learnerB wait, what? If it's classified why did you post it as an image then? — Ch3steR, Jul 21 '20 at 18:09
@Jimmys correct! I cannot figure out how to do this correctly — paytonM, Jul 21 '20 at 18:09
@Ch3steR that is not my actual data. I made it up on excel as an example — paytonM, Jul 21 '20 at 18:10
@learnerB okay, Can you post `df.to_dict()` of the dummy data, it would be easier for everyone to reproduce locally, rather transcribing an image. — Ch3steR, Jul 21 '20 at 18:11
It looks like [**`pd.melt`**](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html). You can try this `df.melt(id_vars=['sex'], value_vars=['name', 'age ']).drop(columns = 'variable')` — Ch3steR, Jul 21 '20 at 18:18
@paytonM No problem. Please go through [How to make good reproducible pandas example](https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples). — Ch3steR, Jul 21 '20 at 18:20

score 0 · Answer 1 · answered Jul 21 '20 at 18:24

One way is to use .append. If your data is in the DataFrame df:

# Split out the relevant parts of your DataFrame
top_df = df[['name','sex']]
bottom_df = df[['age','sex']]

# Make the column names match
bottom_df.columns = ['name','sex']

# Append the two together
full_df = top_df.append(bottom_df)

You might have to decide on what kind of indexing you want. This method above will have non-unique indexing in full_df, which could be fixed by running the following line: full_df.reset_index(drop=True, inplace=True)

score 0 · Answer 2 · answered Jul 21 '20 at 18:29

You can use pd.melt and drop variable column using df.drop here.

df = pd.DataFrame({'Unnamed: 0': {0: np.nan, 1: np.nan, 2: np.nan, 3: np.nan},
                   'age ': {0: 35, 1: 56, 2: 22, 3: 16},
                   'name': {0: 'andrea', 1: 'juan', 2: 'jose ', 3: 'manuel'},
                   'sex': {0: 'female', 1: 'male ', 2: 'male ', 3: 'male '}})

df.melt(id_vars=['sex'], value_vars=['name', 'age']).drop(columns='variable')

      sex   value
0  female  andrea
1   male     juan
2   male    jose
3   male   manuel
4  female      35
5   male       56
6   male       22
7   male       16

Joining two columns in the same data frame

2 Answers2