Merge branch 'master' into ducks-unlimited

CHANGES

@@ -5,6 +5,7 @@ pint-pandas Changelog
 ----------------
 
 - Support for uncertainties as magnitudes in PintArrays. #140
+- Fix dequantify duplicate column failure #202
 - Fix astype issue #196
 
 0.5 (2023-09-07)

docs/getting/index.rst

@@ -7,7 +7,7 @@ The getting started guide aims to get you using pint-pandas productively as quic
 What is Pint-pandas?
 --------------------
 
-The Pandas package provides powerful DataFrame and Series abstractions for dealing with numerical, temporal, categorical, string-based, and even user-defined data (using its ExtensionArray feature). The Pint package provides a rich and extensible vocabulary of units for constructing Quantities and an equally rich and extensible range of unit conversions to make it easy to perform unit-safe calculations using Quantities. Pint-pandas provides PintArray, aPandas ExtensionArray that efficiently implements Pandas DataFrame and Series functionality as unit-aware operations where appropriate.
+The Pandas package provides powerful DataFrame and Series abstractions for dealing with numerical, temporal, categorical, string-based, and even user-defined data (using its ExtensionArray feature). The Pint package provides a rich and extensible vocabulary of units for constructing Quantities and an equally rich and extensible range of unit conversions to make it easy to perform unit-safe calculations using Quantities. Pint-pandas provides PintArray, a Pandas ExtensionArray that efficiently implements Pandas DataFrame and Series functionality as unit-aware operations where appropriate.
 
 Those who have used Pint know well that good units discipline often catches not only simple mistakes, but sometimes more fundamental errors as well. Pint-pandas can reveal similar errors when it comes to slicing and dicing Pandas data.
 

pint_pandas/pint_array.py

@@ -1,7 +1,6 @@
 import copy
 import re
 import warnings
-from collections import OrderedDict
 from importlib.metadata import version
 
 import numpy as np
@@ -1082,23 +1081,35 @@ def formatter_func(dtype):
 
  df_columns = df.columns.to_frame()
  df_columns["units"] = [
- formatter_func(df[col].dtype)
- if isinstance(df[col].dtype, PintType)
+ formatter_func(df.dtypes.iloc[i])
+ if isinstance(df.dtypes.iloc[i], PintType)
  else NO_UNIT
- for col in df.columns
+ for i, col in enumerate(df.columns)
  ]
 
- data_for_df = OrderedDict()
+ data_for_df = []
  for i, col in enumerate(df.columns):
- if isinstance(df[col].dtype, PintType):
- data_for_df[tuple(df_columns.iloc[i])] = df[col].values.data
+ if isinstance(df.dtypes.iloc[i], PintType):
+ data_for_df.append(
+ pd.Series(
+ data=df.iloc[:, i].values.data,
+ name=tuple(df_columns.iloc[i]),
+ index=df.index,
+ copy=False,
+ )
+ )
  else:
- data_for_df[tuple(df_columns.iloc[i])] = df[col].values
-
- df_new = DataFrame(data_for_df, columns=data_for_df.keys())
+ data_for_df.append(
+ pd.Series(
+ data=df.iloc[:, i].values,
+ name=tuple(df_columns.iloc[i]),
+ index=df.index,
+ copy=False,
+ )
+ )
 
+ df_new = pd.concat(data_for_df, axis=1, copy=False)
  df_new.columns.names = df.columns.names + ["unit"]
- df_new.index = df.index
 
  return df_new
 

pint_pandas/testsuite/test_issues.py

@@ -245,3 +245,38 @@ def test_issue_194(dtype):
  s2 = s1.astype(dtype)
 
  tm.assert_series_equal(s0, s2)
+
+
+class TestIssue202(BaseExtensionTests):
+ def test_dequantify(self):
+ df = pd.DataFrame()
+ df["test"] = pd.Series([1, 2, 3], dtype="pint[kN]")
+ df.insert(0, "test", df["test"], allow_duplicates=True)
+
+ expected = pd.DataFrame.from_dict(
+ data={
+ "index": [0, 1, 2],
+ "columns": [("test", "kilonewton")],
+ "data": [[1], [2], [3]],
+ "index_names": [None],
+ "column_names": [None, "unit"],
+ },
+ orient="tight",
+ dtype="Int64",
+ )
+ result = df.iloc[:, 1:].pint.dequantify()
+ tm.assert_frame_equal(expected, result)
+
+ expected = pd.DataFrame.from_dict(
+ data={
+ "index": [0, 1, 2],
+ "columns": [("test", "kilonewton"), ("test", "kilonewton")],
+ "data": [[1, 1], [2, 2], [3, 3]],
+ "index_names": [None],
+ "column_names": [None, "unit"],
+ },
+ orient="tight",
+ dtype="Int64",
+ )
+ result = df.pint.dequantify()
+ tm.assert_frame_equal(expected, result)