I have a dataframe that looks like this:
| class_id | dims |
|---|---|
| 94369_GA_30122 | 95 |
| 27369_GA_30122 | 14 |
| 78369_CA_30122 | 27 |
| 30472_MN_55121 | 16 |
and the dataframe goes on... I want to sort my column class_id numerically ascending, that is itt must look like
| class_id | dims |
|---|---|
| 27369_GA_30122 | 14 |
| 30472_MN_55121 | 16 |
| 78369_CA_30122 | 27 |
| 94369_GA_30122 | 95 |
can anyone tell me how can I achieve this?
I believe this should do the trick:
data = {"class_id": ["94369_GA_30122", "27369_GA_30122", "78369_CA_30122", "30472_MN_55121"],
"dims": [95, 14, 27, 16]}
df = pd.DataFrame(data)
df = df.sort_values("class_id")
Out:
class_id dims
1 27369_GA_30122 14
3 30472_MN_55121 16
2 78369_CA_30122 27
0 94369_GA_30122 95
Edit: You can also add these lines to only sort on the first set of numbers.
df["sorting"] = df["class_id"].str.split("_", n=1).str[0] # Extracting only the first set of numbers
df = df.sort_values("sorting")
df = df.drop("sorting", axis=1) # To drop the column again
https://pandas.pydata.org/docs/reference/api/pandas.Series.str.split.html
If you want to sort the value by class_id :
df.sort_values(by=['class_id'])
If you want to sort the value by dims :
df.sort_values(by=['dims'])
Tf you want to sort based on both you can use :
df.sort_values(by=['class_id', 'dims'])
you can refer from this site - https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html
