I want to reorder dataframe columns from a subclassed pandas dataframe.
I understood from this question there might be a better way for not subclassing a dataframe, but I'm still wondering how to approach this.
Without subclassing, I would do it in a classic way:
import pandas as pd
data = {'Description':['mydesc'], 'Name':['myname'], 'Symbol':['mysymbol']}
df = pd.DataFrame(data)
df = df[['Symbol', 'Name', 'Description']]
But with subclassing, keeping the same behavior as the classic one doesn't reorder the columns:
import pandas as pd
class SubDataFrame(pd.DataFrame):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self = self._reorder_columns()
def _reorder_columns(self):
first_columns = ['Symbol', 'Name', 'Description']
return self[first_columns + [c for c in self.columns if c not in first_columns]]
data = {'Description':['mydesc'], 'Name':['myname'], 'Symbol':['mysymbol']}
df = SubDataFrame(data)
I believe my mistake is in reassigning self
which doesn't have any effect.
How can I achieve column reordering on the subclassed dataframe?
Pandas methods that have an inplace
parameter use the private method _update_inplace
. You could do the same, but be sure to follow future pandas development in case this method changes:
import pandas as pd
class SubDataFrame(pd.DataFrame):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._update_inplace(self._reorder_columns())
def _reorder_columns(self):
first_columns = ['Symbol', 'Name', 'Description']
return self[first_columns + [c for c in self.columns if c not in first_columns]]
data = {'Description':['mydesc'], 'Name':['myname'], 'Symbol':['mysymbol']}
df = SubDataFrame(data)
Output:
Symbol Name Description
0 mysymbol myname mydesc