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2 changes: 1 addition & 1 deletion pandas/core/algorithms.py
Original file line number Diff line number Diff line change
Expand Up @@ -223,7 +223,7 @@ def quantile(x, q, interpolation_method='fraction'):
score : float
Score at percentile.

Examplesb
Examples
--------
>>> from scipy import stats
>>> a = np.arange(100)
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6 changes: 3 additions & 3 deletions pandas/core/frame.py
Original file line number Diff line number Diff line change
Expand Up @@ -1161,7 +1161,7 @@ def to_excel(self, excel_writer, sheet_name='sheet1', na_rep='',
sheet_name : string, default 'sheet1'
Name of sheet which will contain DataFrame
na_rep : string, default ''
Missing data rep'n
Missing data representation
cols : sequence, optional
Columns to write
header : boolean or list of string, default True
Expand Down Expand Up @@ -4303,7 +4303,7 @@ def _reduce(self, op, axis=0, skipna=True, numeric_only=None,

def idxmin(self, axis=0, skipna=True):
"""
Return index of first occurence of minimum over requested axis.
Return index of first occurrence of minimum over requested axis.
NA/null values are excluded.

Parameters
Expand All @@ -4325,7 +4325,7 @@ def idxmin(self, axis=0, skipna=True):

def idxmax(self, axis=0, skipna=True):
"""
Return index of first occurence of maximum over requested axis.
Return index of first occurrence of maximum over requested axis.
NA/null values are excluded.

Parameters
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/groupby.py
Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ class GroupBy(object):
-----
After grouping, see aggregate, apply, and transform functions. Here are
some other brief notes about usage. When grouping by multiple groups, the
result index will be a MultiIndex (hierarhical) by default.
result index will be a MultiIndex (hierarchical) by default.

Iteration produces (key, group) tuples, i.e. chunking the data by group. So
you can write code like:
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/index.py
Original file line number Diff line number Diff line change
Expand Up @@ -2291,7 +2291,7 @@ def insert(self, loc, item):
new_index : Index
"""
if not isinstance(item, tuple) or len(item) != self.nlevels:
raise Exception("%s cannot be inserted in this MultIndex"
raise Exception("%s cannot be inserted in this MultiIndex"
% str(item))

new_levels = []
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2 changes: 1 addition & 1 deletion pandas/core/panel.py
Original file line number Diff line number Diff line change
Expand Up @@ -487,7 +487,7 @@ def to_excel(self, path, na_rep=''):
excel_writer : string or ExcelWriter object
File path or existing ExcelWriter
na_rep : string, default ''
Missing data rep'n
Missing data representation
"""
from pandas.io.parsers import ExcelWriter
writer = ExcelWriter(path)
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16 changes: 8 additions & 8 deletions pandas/core/series.py
Original file line number Diff line number Diff line change
Expand Up @@ -752,7 +752,7 @@ def set_value(self, label, value):

def reset_index(self, drop=False, name=None):
"""
Analagous to the DataFrame.reset_index function, see docstring there.
Analogous to the DataFrame.reset_index function, see docstring there.

Parameters
----------
Expand Down Expand Up @@ -1139,7 +1139,7 @@ def _agg_by_level(self, name, level=0, skipna=True, **kwds):

def idxmin(self, axis=None, out=None, skipna=True):
"""
Index of first occurence of minimum of values.
Index of first occurrence of minimum of values.

Parameters
----------
Expand All @@ -1148,7 +1148,7 @@ def idxmin(self, axis=None, out=None, skipna=True):

Returns
-------
idxmin : Index of mimimum of values
idxmin : Index of minimum of values
"""
i = nanops.nanargmin(self.values, skipna=skipna)
if i == -1:
Expand All @@ -1157,7 +1157,7 @@ def idxmin(self, axis=None, out=None, skipna=True):

def idxmax(self, axis=None, out=None, skipna=True):
"""
Index of first occurence of maximum of values.
Index of first occurrence of maximum of values.

Parameters
----------
Expand All @@ -1166,7 +1166,7 @@ def idxmax(self, axis=None, out=None, skipna=True):

Returns
-------
idxmax : Index of mimimum of values
idxmax : Index of minimum of values
"""
i = nanops.nanargmax(self.values, skipna=skipna)
if i == -1:
Expand Down Expand Up @@ -1757,7 +1757,7 @@ def order(self, na_last=True, ascending=True, kind='mergesort'):
Sort ascending. Passing False sorts descending
kind : {'mergesort', 'quicksort', 'heapsort'}, default 'mergesort'
Choice of sorting algorithm. See np.sort for more
information. 'mergesort' is the only stable algorith
information. 'mergesort' is the only stable algorithm

Returns
-------
Expand Down Expand Up @@ -2341,7 +2341,7 @@ def to_csv(self, path, index=True, sep=",", na_rep='', header=False,
----------
path : string file path or file handle / StringIO
na_rep : string, default ''
Missing data rep'n
Missing data representation
header : boolean, default False
Write out series name
index : boolean, default True
Expand Down Expand Up @@ -2465,7 +2465,7 @@ def asof(self, where):

Parameters
----------
wehre : date or array of dates
where : date or array of dates

Notes
-----
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/strings.py
Original file line number Diff line number Diff line change
Expand Up @@ -417,7 +417,7 @@ def str_findall(arr, pat, flags=0):
Parameters
----------
pat : string
Pattern or regular expressino
Pattern or regular expression
flags : int, default 0 (no flags)
re module flags, e.g. re.IGNORECASE

Expand Down
2 changes: 1 addition & 1 deletion pandas/sparse/frame.py
Original file line number Diff line number Diff line change
Expand Up @@ -253,7 +253,7 @@ def density(self):
return tot_nonsparse / float(tot)

#----------------------------------------------------------------------
# Support different internal rep'n of SparseDataFrame
# Support different internal representation of SparseDataFrame

def _set_item(self, key, value):
sp_maker = lambda x: SparseSeries(x, index=self.index,
Expand Down
4 changes: 2 additions & 2 deletions pandas/stats/misc.py
Original file line number Diff line number Diff line change
Expand Up @@ -141,7 +141,7 @@ def bucketcat(series, cats):
----------
series : Series
cat : Series or same-length array
bucket by category; mutually exxlusive with 'by'
bucket by category; mutually exclusive with 'by'

Returns
-------
Expand Down Expand Up @@ -175,7 +175,7 @@ def bucketpanel(series, bins=None, by=None, cat=None):
by : tuple of Series
bucket by value
cat : tuple of Series
bucket by category; mutually exxlusive with 'by'
bucket by category; mutually exclusive with 'by'

Returns
-------
Expand Down
8 changes: 4 additions & 4 deletions pandas/tools/plotting.py
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ def scatter_matrix(frame, alpha=0.5, figsize=None, ax=None, grid=False,
grid : setting this to True will show the grid
diagonal : pick between 'kde' and 'hist' for
either Kernel Density Estimation or Histogram
plon in the diagonal
plot in the diagonal
kwds : other plotting keyword arguments
To be passed to scatter function

Expand Down Expand Up @@ -1304,7 +1304,7 @@ def plot_series(series, label=None, kind='line', use_index=True, rot=None,
def boxplot(data, column=None, by=None, ax=None, fontsize=None,
rot=0, grid=True, figsize=None, **kwds):
"""
Make a box plot from DataFrame column optionally grouped b ysome columns or
Make a box plot from DataFrame column optionally grouped by some columns or
other inputs

Parameters
Expand Down Expand Up @@ -1733,7 +1733,7 @@ def _subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True,
- for NxM subplots with N>1 and M>1 are returned as a 2d array.

If False, no squeezing at all is done: the returned axis object is always
a 2-d array contaning Axis instances, even if it ends up being 1x1.
a 2-d array containing Axis instances, even if it ends up being 1x1.

subplot_kw : dict
Dict with keywords passed to the add_subplot() call used to create each
Expand All @@ -1753,7 +1753,7 @@ def _subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True,
fig, ax : tuple
- fig is the Matplotlib Figure object
- ax can be either a single axis object or an array of axis objects if
more than one supblot was created. The dimensions of the resulting array
more than one subplot was created. The dimensions of the resulting array
can be controlled with the squeeze keyword, see above.

**Examples:**
Expand Down
2 changes: 1 addition & 1 deletion pandas/tseries/frequencies.py
Original file line number Diff line number Diff line change
Expand Up @@ -703,7 +703,7 @@ def infer_freq(index, warn=True):
Returns
-------
freq : string or None
None if no discernable frequency
None if no discernible frequency
"""
from pandas.tseries.index import DatetimeIndex

Expand Down
2 changes: 1 addition & 1 deletion pandas/tseries/index.py
Original file line number Diff line number Diff line change
Expand Up @@ -602,7 +602,7 @@ def order(self, return_indexer=False, ascending=True):

def snap(self, freq='S'):
"""
Snap time stamps to nearest occuring frequency
Snap time stamps to nearest occurring frequency

"""
# Superdumb, punting on any optimizing
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2 changes: 1 addition & 1 deletion pandas/tseries/offsets.py
Original file line number Diff line number Diff line change
Expand Up @@ -529,7 +529,7 @@ class WeekOfMonth(DateOffset, CacheableOffset):
0 is 1st week of month, 1 2nd week, etc.
weekday : {0, 1, ..., 6}
0: Mondays
1: Tuedays
1: Tuesdays
2: Wednesdays
3: Thursdays
4: Fridays
Expand Down