🔒 I need help with join 2 dataframes

[blazing stirrup]

@arctic berry

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[arctic berry]

When i try do it, it looks very weird

age sex cp trestbps chol fbs restecg thalach exang oldpeak ...
0 63 1 1 145 233 1 2 150 0 2.3 ...
0 55 1 1 140 244 0 2 138 0 2.3 ...
0 66 0 4 160 255 0 0 172 1 1.4 ...
1 67 1 4 160 286 0 2 108 1 1.5 ...
2 67 1 4 120 229 0 2 129 1 2.6 ...
.. ... ... .. ... ... ... ... ... ... ... ...
298 52 1 1 118 186 0 2 190 0 0.0 ...
299 43 0 4 132 341 1 2 136 1 3.0 ...
300 65 1 4 135 254 0 2 127 0 2.8 ...
301 48 1 4 130 256 1 2 150 1 0.0 ...
302 63 0 4 150 407 0 2 154 0 4.0 ...

 additional_chol_additional  additional_fbs_additional  \

0 220.0 1.0
0 220.0 1.0
0 220.0 1.0
1 240.0 0.0
2 260.0 1.0
.. ... ...
298 NaN NaN
299 NaN

additional same colums, i dont understand how to make information be in same ones

with join

[copper sequoia]

That's fine, the \ just means that it deemed the df too long to be displayed on one line so it split it into multiple when printing
In reality it's just one big 2d table

[arctic berry]

no,no, i meant additional_fbs_additional, i want it be just in colum fbs

this information, i dont want creat new ones

[copper quail]

@arctic berry what are the names of the two dataframes?

[arctic berry]

result = result.join(additional_data, rsuffix='_right') i try that but

[copper sequoia]

can you also show the code you're using? maybe the 2 dfs' columns you're trying to join as well

[copper quail]

so the names are result and additional_data?

[arctic berry]

yea

additional_data = pd.DataFrame({
'age': [40, 35, 50],
'sex': [0, 1, 1],
'cp': [2, 3, 1],
'trestbps': [130, 125, 140],
'chol': [220, 240, 260],
'fbs': [1, 0, 1],
'restecg': [0, 1, 2],
'thalach': [150, 155, 160],
'exang': [0, 1, 0],
'oldpeak': [1.0, 1.5, 2.0],
'slope': [1, 2, 2],
'ca': [0, 1, 0],
'thal': ['fixed', 'reversible', 'normal'],
'target': [0, 1, 0]
})
result = result.join(additional_data, rsuffix='_right') and other data frame in file csv

[copper quail]

@arctic berry please show the result of print(result.index)

though it looks like these are additional rows you want to add. whereas join and merge are for adding columns.

so you need to use pd.concat

[strange field]

I think you're looking for pd.concat, yeah

[arctic berry]

Index([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
...
295, 296, 297, 298, 299, 300, 301, 302, 0, 0],
dtype='int64', length=305)

[copper quail]

!docs pandas.concat

[blazing stirrup]

pandas.concat

pandas.concat(objs, *, axis=0, join='outer', ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=False, copy=None)```
Concatenate pandas objects along a particular axis.

Allows optional set logic along the other axes.

Can also add a layer of hierarchical indexing on the concatenation axis, which may be useful if the labels are the same (or overlapping) on the passed axis number.

[arctic berry]

i mean, i can but task make me do it with join

xd

i did it with contat before, but this one asked with join

[copper quail]

either there's some confusion about what the actual task is, or they've asked you to do an impossible thing

[arctic berry]

Create another DataFrame structure, fill it with arbitrary data and connect it vertically with the current structure (join). thats the task

i think most second, that they asked for impossible thing bc i tried everything

with join

[copper sequoia]

transpose, join, transpose back

[copper quail]

"arbitrary data" is a key detail.
Don't use the same column names as before.

you also need as many rows as there are rows in the dataframe you want to join to.

(at least ideally.)

[arctic berry]

so i need make completely new columns?

[copper quail]

well, why would you want two age columns in the same dataframe? what would that even mean?

if each row represents a person, how would they have more than one age?

[arctic berry]

well. true

i think i get it, let me try

[blazing stirrup]

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