internlm/SWE-Fixer-Train-110K huggingface dataset:
Repository: modin-project/modin

Issue:
AttributeError:	list' object has no attribute 'reindex'

### Describe the problem
<!-- Describe the problem clearly here. -->
When inserting a new column, we do not correctly check the type of the object before reindexing.

### Source code / logs

`data["speed_level"] = ["high" if i > threshold else "low" for i in data.Speed]`
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/data_management/query_compiler/pandas_query_compiler.py b/modin/data_management/query_compiler/pandas_query_compiler.py
--- a/modin/data_management/query_compiler/pandas_query_compiler.py
+++ b/modin/data_management/query_compiler/pandas_query_compiler.py
@@ -2288,7 +2288,9 @@ def insert(self, loc, column, value):
             A new PandasQueryCompiler with new data inserted.
         """
         if is_list_like(value):
-            if hasattr(value, "index"):
+            from modin.pandas.series import SeriesView
+
+            if isinstance(value, (pandas.Series, SeriesView)):
                 value = value.reindex(self.index)
             value = list(value)
 


Test patch:
Repository: modin-project/modin

Issue:
AttributeError: module 'modin.pandas' has no attribute 'crosstab'

### Describe the problem
<!-- Describe the problem clearly here. -->
`crosstab` is not currently in the `modin.pandas` module. We can default to pandas for this.

### Source code / logs

```python
import modin.pandas as pd
pd.crosstab(args)
```
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/__init__.py b/modin/pandas/__init__.py
--- a/modin/pandas/__init__.py
+++ b/modin/pandas/__init__.py
@@ -58,7 +58,7 @@
     read_gbq,
     read_table,
 )
-from .reshape import get_dummies, melt
+from .reshape import get_dummies, melt, crosstab
 from .general import isna, merge, pivot_table
 from .. import __execution_engine__ as execution_engine
 
@@ -155,6 +155,7 @@
     "Categorical",
     "__version__",
     "melt",
+    "crosstab",
 ]
 
 del pandas
diff --git a/modin/pandas/reshape.py b/modin/pandas/reshape.py
--- a/modin/pandas/reshape.py
+++ b/modin/pandas/reshape.py
@@ -6,6 +6,7 @@
 from pandas.core.dtypes.common import is_list_like
 
 from .dataframe import DataFrame
+from modin.error_message import ErrorMessage
 
 
 def get_dummies(
@@ -78,3 +79,31 @@ def melt(
         value_name=value_name,
         col_level=col_level,
     )
+
+
+def crosstab(
+    index,
+    columns,
+    values=None,
+    rownames=None,
+    colnames=None,
+    aggfunc=None,
+    margins=False,
+    margins_name="All",
+    dropna=True,
+    normalize=False,
+):
+    ErrorMessage.default_to_pandas()
+    pandas_crosstab = pandas.crosstab(
+        index,
+        columns,
+        values,
+        rownames,
+        colnames,
+        aggfunc,
+        margins,
+        margins_name,
+        dropna,
+        normalize,
+    )
+    return DataFrame(pandas_crosstab)


Test patch:
Repository: modin-project/modin

Issue:
df.align returns a pandas DataFrame instead of a Modin DataFrame

### Describe the problem
<!-- Describe the problem clearly here. -->
`df.align` returns a pandas DataFrame instead of a Modin DataFrame

### Source code / logs
`type(df.align(args)[0])`
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -5023,4 +5023,16 @@ def _default_to_pandas(self, op, *args, **kwargs):
         if isinstance(result, pandas.DataFrame):
             return DataFrame(result)
         else:
-            return result
+            try:
+                if len(result) == 2 and isinstance(result[0], pandas.DataFrame):
+                    # Some operations split the DataFrame into two (e.g. align). We need to wrap
+                    # both of the returned results
+                    if isinstance(result[1], pandas.DataFrame):
+                        second = DataFrame(result[1])
+                    else:
+                        second = result[1]
+                    return DataFrame(result[0]), second
+                else:
+                    return result
+            except TypeError:
+                return result


Test patch:
Repository: modin-project/modin

Issue:
TypeError: bad operand type for abs(): 'SeriesView'

### Describe the problem
<!-- Describe the problem clearly here. -->
SeriesView does not implement the `__abs__` operator yet, but Series does. Since this is a builtin, it cannot default back and must be implemented.

### Source code / logs
`abs(df['col1'])`
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/series.py b/modin/pandas/series.py
--- a/modin/pandas/series.py
+++ b/modin/pandas/series.py
@@ -147,6 +147,9 @@ def __ipow__(self, other):
     def __neg__(self, other):
         return self.__arithmetic_op__("__neg__")(other)
 
+    def __abs__(self):
+        return self.series.abs()
+
     def __iter__(self):
         return self.series.__iter__()
 


Test patch:
Repository: modin-project/modin

Issue:
AttributeError: 'function' object has no attribute 'hist'

### Describe the problem
We have to handle classes separately in `SeriesView` objects.
<!-- Describe the problem clearly here. -->
```
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~/Downloads/kaggle7/kaggle7.py in <module>
    126 # In[16]:
    127 
--> 128 app_train['DAYS_EMPLOYED'].plot.hist(title = 'Days Employment Histogram');
    129 plt.xlabel('Days Employment');
    130 

AttributeError: 'function' object has no attribute 'hist'
```
### Source code / logs
`df['col1'].plot.hist(...)`
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/series.py b/modin/pandas/series.py
--- a/modin/pandas/series.py
+++ b/modin/pandas/series.py
@@ -178,8 +178,13 @@ def __getattribute__(self, item):
             # cannot be overridden with the functions below. This generally solves the
             # problem where the instance property is callable, but the class property is
             # not.
-            is_callable = callable(method) and callable(
-                getattr(type(self.series), item)
+            # The isclass check is to ensure that we return the correct type. Some of
+            # the objects that are called result in classes being returned, and we don't
+            # want to override with our own function.
+            is_callable = (
+                callable(method)
+                and callable(getattr(type(self.series), item))
+                and not inspect.isclass(getattr(type(self.series), item))
             )
             try:
                 has_inplace_param = is_callable and "inplace" in str(


Test patch:
Repository: modin-project/modin

Issue:
drop is extremely slow when dropping many columns

### Describe the problem
<!-- Describe the problem clearly here. -->
`drop` can be very slow when dropping many columns/rows. It is caused be inefficiently computing the index in post-processing.

### Source code / logs
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->
```python
df.drop(index=df.index[[True for _ in range(len(df) - 1)] + [False]])
```


Discussion:

Resolving patch:
diff --git a/modin/data_management/query_compiler/pandas_query_compiler.py b/modin/data_management/query_compiler/pandas_query_compiler.py
--- a/modin/data_management/query_compiler/pandas_query_compiler.py
+++ b/modin/data_management/query_compiler/pandas_query_compiler.py
@@ -1652,7 +1652,6 @@ def diff(self, **kwargs):
 
     def dropna(self, **kwargs):
         """Returns a new DataManager with null values dropped along given axis.
-
         Return:
             a new DataManager
         """
@@ -2253,11 +2252,7 @@ def delitem(df, internal_indices=[]):
             )
             # We can't use self.index.drop with duplicate keys because in Pandas
             # it throws an error.
-            new_index = [
-                self.index[i]
-                for i in range(len(self.index))
-                if i not in numeric_indices
-            ]
+            new_index = self.index[~self.index.isin(index)]
         if columns is None:
             new_columns = self.columns
             new_dtypes = self.dtypes
@@ -2270,13 +2265,8 @@ def delitem(df, internal_indices=[]):
             new_data = new_data.apply_func_to_select_indices(
                 0, delitem, numeric_indices, keep_remaining=True
             )
-            # We can't use self.columns.drop with duplicate keys because in Pandas
-            # it throws an error.
-            new_columns = [
-                self.columns[i]
-                for i in range(len(self.columns))
-                if i not in numeric_indices
-            ]
+
+            new_columns = self.columns[~self.columns.isin(columns)]
             new_dtypes = self.dtypes.drop(columns)
         return self.__constructor__(new_data, new_index, new_columns, new_dtypes)
 


Test patch:
Repository: modin-project/modin

Issue:
Correctness regression on DataFrames with 2 rows

### Describe the problem
<!-- Describe the problem clearly here. -->
This is an interesting one, it was caused by #371. Basically we need to improve the error checking. It is a simple fix. Most operations for that size are broken because of [this](https://github.com/modin-project/modin/blame/master/modin/pandas/dataframe.py#L5038)

### Source code / logs
```python
import modin.pandas as pd
df = pd.DataFrame({"col1":[1,2], "col2":[2,3]})
print(df['col1'])
```

<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -5035,7 +5035,11 @@ def _default_to_pandas(self, op, *args, **kwargs):
             return DataFrame(result)
         else:
             try:
-                if len(result) == 2 and isinstance(result[0], pandas.DataFrame):
+                if (
+                    isinstance(result, (list, tuple))
+                    and len(result) == 2
+                    and isinstance(result[0], pandas.DataFrame)
+                ):
                     # Some operations split the DataFrame into two (e.g. align). We need to wrap
                     # both of the returned results
                     if isinstance(result[1], pandas.DataFrame):


Test patch:
Repository: modin-project/modin

Issue:
TypeError: hist() missing 1 required positional argument: 'data'

### Describe the problem
<!-- Describe the problem clearly here. -->
It seems that some of the pandas documentation is a bit confusing about the arguments for this function, but it does not have a `data` parameter even though we require one.

### Source code / logs

```python
...
df.hist()
```
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -1740,7 +1740,6 @@ def head(self, n=5):
 
     def hist(
         self,
-        data,
         column=None,
         by=None,
         grid=True,
@@ -1758,7 +1757,6 @@ def hist(
     ):
         return self._default_to_pandas(
             pandas.DataFrame.hist,
-            data,
             column=column,
             by=by,
             grid=grid,


Test patch:
Repository: modin-project/modin

Issue:
AttributeError: module 'modin.pandas' has no attribute 'plotting'

### Describe the problem
<!-- Describe the problem clearly here. -->
We do not have a `plotting` module, which is sometimes used to plot things. These will default to pandas.

### Source code / logs

```python
import modin.pandas as pd
pd.plotting.boxplot(...)
```
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/__init__.py b/modin/pandas/__init__.py
--- a/modin/pandas/__init__.py
+++ b/modin/pandas/__init__.py
@@ -60,6 +60,7 @@
 )
 from .reshape import get_dummies, melt, crosstab
 from .general import isna, merge, pivot_table
+from .plotting import Plotting as plotting
 from .. import __execution_engine__ as execution_engine
 
 __pandas_version__ = "0.23.4"
@@ -156,6 +157,7 @@
     "__version__",
     "melt",
     "crosstab",
+    "plotting",
 ]
 
 del pandas
diff --git a/modin/pandas/plotting.py b/modin/pandas/plotting.py
new file mode 100644
--- /dev/null
+++ b/modin/pandas/plotting.py
@@ -0,0 +1,46 @@
+from pandas import plotting as pdplot
+
+from .utils import to_pandas
+from .dataframe import DataFrame
+
+
+def instancer(cls):
+    """This will create a dummy instance each time this is imported.
+
+    This serves the purpose of allowing us to use all of pandas plotting methods without
+        aliasing and writing each of them ourselves.
+    """
+    return cls()
+
+
+@instancer
+class Plotting(object):
+    def __dir__(self):
+        """This allows tab completion of plotting library"""
+        return dir(pdplot)
+
+    def __getattribute__(self, item):
+        """This method will override the parameters passed and convert any Modin
+            DataFrames to pandas so that they can be plotted normally
+        """
+        if hasattr(pdplot, item):
+            func = getattr(pdplot, item)
+            if callable(func):
+
+                def wrap_func(*args, **kwargs):
+                    """Convert Modin DataFrames to pandas then call the function"""
+                    args = tuple(
+                        arg if not isinstance(arg, DataFrame) else to_pandas(arg)
+                        for arg in args
+                    )
+                    kwargs = {
+                        kwd: val if not isinstance(val, DataFrame) else to_pandas(val)
+                        for kwd, val in kwargs.items()
+                    }
+                    return func(*args, **kwargs)
+
+                return wrap_func
+            else:
+                return func
+        else:
+            return object.__getattribute__(self, item)


Test patch:
Repository: modin-project/modin

Issue:
df.dtypes after df.iloc does not match Pandas behavior
After a call to `df.iloc` which sets an item in a column with a different `dtype`, the item being added is cast incorrectly. As a result, the DataFrame after `iloc` as well as its `dtypes` are incorrect.



Discussion:
Adding some caveats to this issue:

The problem only really arises when the `dtypes` are already cached. The problem is coming from `PandasQueryCompilerView` objects not having a custom way to deal with `dtypes`.

Resolving patch:
diff --git a/modin/data_management/query_compiler/pandas_query_compiler.py b/modin/data_management/query_compiler/pandas_query_compiler.py
--- a/modin/data_management/query_compiler/pandas_query_compiler.py
+++ b/modin/data_management/query_compiler/pandas_query_compiler.py
@@ -2718,6 +2718,27 @@ def __init__(
             self, block_partitions_object, index, columns, dtypes
         )
 
+    _dtype_cache = None
+
+    def _set_dtype(self, dtypes):
+        self._dtype_cache = dtypes
+
+    def _get_dtype(self):
+        """Override the parent on this to avoid getting the wrong dtypes"""
+        if self._dtype_cache is None:
+            map_func = self._prepare_method(lambda df: df.dtypes)
+
+            def dtype_builder(df):
+                return df.apply(lambda row: find_common_type(row.values), axis=0)
+
+            self._dtype_cache = self.data.full_reduce(map_func, dtype_builder, 0)
+            self._dtype_cache.index = self.columns
+        elif not self._dtype_cache.index.equals(self.columns):
+            self._dtype_cache = self._dtype_cache.reindex(self.columns)
+        return self._dtype_cache
+
+    dtypes = property(_get_dtype, _set_dtype)
+
     def __constructor__(
         self,
         block_partitions_object: BaseBlockPartitions,


Test patch:
Repository: modin-project/modin

Issue:
df.iloc[...].iloc[...] does not match pandas behavior and sometimes throws an error

### Describe the problem
<!-- Describe the problem clearly here. -->
This was discovered after running a scikitlearn workflow on a DataFrame that was the result of an `loc` (code below).

### Source code / logs

```python
x, y = df.loc[:, df.columns != "filter"], df.loc[:, "filter"]
from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test = train_test_split(x,y,test_size = 0.3,random_state = 1)
knn = KNeighborsClassifier(n_neighbors = 3)
x,y = data.loc[:,data.columns != 'class'], data.loc[:,'class']
knn.fit(x_train,y_train)
prediction = knn.predict(x_test)
```
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/data_management/query_compiler/pandas_query_compiler.py b/modin/data_management/query_compiler/pandas_query_compiler.py
--- a/modin/data_management/query_compiler/pandas_query_compiler.py
+++ b/modin/data_management/query_compiler/pandas_query_compiler.py
@@ -2712,7 +2712,6 @@ def __init__(
 
         self.index_map = index_map_series
         self.columns_map = columns_map_series
-        self.is_view = True
 
         PandasQueryCompiler.__init__(
             self, block_partitions_object, index, columns, dtypes
diff --git a/modin/pandas/indexing.py b/modin/pandas/indexing.py
--- a/modin/pandas/indexing.py
+++ b/modin/pandas/indexing.py
@@ -147,18 +147,13 @@ class _LocationIndexerBase(object):
     def __init__(self, ray_df: DataFrame):
         self.df = ray_df
         self.qc = ray_df._query_compiler
-        self.is_view = hasattr(self.qc, "is_view")
-
         self.row_scaler = False
         self.col_scaler = False
 
     def __getitem__(
         self, row_lookup: pandas.Index, col_lookup: pandas.Index, ndim: int
     ):
-        if self.is_view:
-            qc_view = self.qc.__constructor__(self.qc.data, row_lookup, col_lookup)
-        else:
-            qc_view = self.qc.view(row_lookup, col_lookup)
+        qc_view = self.qc.view(row_lookup, col_lookup)
 
         if ndim == 2:
             return DataFrame(query_compiler=qc_view)


Test patch:
Repository: modin-project/modin

Issue:
AttributeError: module 'modin.pandas' has no attribute 'isnull'

### Describe the problem
<!-- Describe the problem clearly here. -->
`modin.pandas` is missing the `isnull` function that `pandas` has. `df.isnull` is implemented, but `pd.isnull` is not. `pd.isna` has been implemented, and they both use the same code in pandas, so we can just alias `isnull` to `isna`.

### Source code / logs

```python
import modin.pandas as pd
pd.isnull(df)
```
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/__init__.py b/modin/pandas/__init__.py
--- a/modin/pandas/__init__.py
+++ b/modin/pandas/__init__.py
@@ -59,7 +59,7 @@
     read_table,
 )
 from .reshape import get_dummies, melt, crosstab
-from .general import isna, merge, pivot_table
+from .general import isna, isnull, merge, pivot_table
 from .plotting import Plotting as plotting
 from .. import __execution_engine__ as execution_engine
 
@@ -135,6 +135,7 @@
     "to_datetime",
     "get_dummies",
     "isna",
+    "isnull",
     "merge",
     "pivot_table",
     "Panel",
diff --git a/modin/pandas/general.py b/modin/pandas/general.py
--- a/modin/pandas/general.py
+++ b/modin/pandas/general.py
@@ -22,6 +22,9 @@ def isna(obj):
         return pandas.isna(obj)
 
 
+isnull = isna
+
+
 def merge(
     left,
     right,


Test patch:
Repository: modin-project/modin

Issue:
insert does not support inserting DataFrame objects

### Describe the problem
<!-- Describe the problem clearly here. -->
Modin is not supporting a feature of pandas that lets you pass a DataFrame as the `value` in `df.insert`.

The code example uses `__setitem__`, which calls `insert.

### Source code / logs

`data['Initial']=data.Name.str.extract('([A-Za-z]+)\.')`
<!-- Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem. -->



Discussion:

Resolving patch:
diff --git a/modin/pandas/dataframe.py b/modin/pandas/dataframe.py
--- a/modin/pandas/dataframe.py
+++ b/modin/pandas/dataframe.py
@@ -1937,7 +1937,10 @@ def insert(self, loc, column, value, allow_duplicates=False):
             value (int, Series, or array-like): The values to insert.
             allow_duplicates (bool): Whether to allow duplicate column names.
         """
-
+        if isinstance(value, (DataFrame, pandas.DataFrame)):
+            if len(value.columns) != 1:
+                raise ValueError("Wrong number of items passed 2, placement implies 1")
+            value = value.iloc[:, 0]
         if len(self.index) == 0:
             try:
                 value = pandas.Series(value)


Test patch: