Data | Indexing with list with missing labels is deprecated in Pandas
date
Apr 12, 2020
slug
index-missing-label-deprecated-pandas
status
Published
summary
For
.reindex , from 0.21.0, .loc or [] are not allowed to index with a list with one or more missing labels in Pandas。tags
Academic
Data Analysis
Python
Pandas
type
Post
For
.reindex , from 0.21.0, .loc or [] are not allowed to index with a list with one or more missing labels in Pandas。Starting in 0.21.0, using .loc or [] with a list with one or more missing labels, is deprecated, in favor of .reindex.
i.e.
s = pd.Series([1, 2, 3])
In [99]: s
Out[99]:
0 1
1 2
2 3
dtype: int64Before
Simple:
s.loc[[1, 2, 3]]Get：
Out[4]:
1 2.0
2 3.0
3 NaN
dtype: float64After
Now, we only get:
In [4]: s.loc[[1, 2, 3]]
Passing list-likes to .loc with any non-matching elements will raise
KeyError in the future, you can use .reindex() as an alternative.
See the documentation here:
https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
Out[4]:
1 2.0
2 3.0
3 NaN
dtype: float64Similar behavior in a simple way
In current version (>0.21.0), we can use
.reindex to get expected result as before, according to the official document：s.reindex([1, 2, 3])In DataFrame, similar:
df.reindex([1, 2, 3], axix=1) # 列More examples are listed here。
Pandas updates a lot~~~ : (