def to_X(self, dataframe: DataFrame) -> DataFrame:
dataframe = dataframe.drop(columns=self.params['Y_field'],
errors='ignore')
dataframe = self.X_features(dataframe)
# noinspection PyProtectedMember
dataframe = dataframe._get_numeric_data(
) # BUGFIX: Linear Regression Crashes if provided with non-numeric inputs
dataframe = dataframe.fillna(
0) # allow X_features() to do custom fillna() first
return dataframe
def boxplot(data, column=None, by=None, ax=None, fontsize=None,
rot=0, grid=True, figsize=None):
"""
Make a box plot from DataFrame column optionally grouped b ysome columns or
other inputs
Parameters
----------
data : DataFrame or Series
column : column name or list of names, or vector
Can be any valid input to groupby
by : string or sequence
Column in the DataFrame to group by
fontsize : int or string
Returns
-------
ax : matplotlib.axes.AxesSubplot
"""
from pandas import Series, DataFrame
if isinstance(data, Series):
data = DataFrame({'x' : data})
column = 'x'
def plot_group(grouped, ax):
keys, values = zip(*grouped)
keys = [_stringify(x) for x in keys]
ax.boxplot(values)
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
if column == None:
columns = None
else:
if isinstance(column, (list, tuple)):
columns = column
else:
columns = [column]
if by is not None:
if not isinstance(by, (list, tuple)):
by = [by]
fig, axes = _grouped_plot_by_column(plot_group, data, columns=columns,
by=by, grid=grid, figsize=figsize)
# Return axes in multiplot case, maybe revisit later # 985
ret = axes
else:
if ax is None:
ax = _gca()
fig = ax.get_figure()
data = data._get_numeric_data()
if columns:
cols = columns
else:
cols = data.columns
keys = [_stringify(x) for x in cols]
# Return boxplot dict in single plot case
bp = ax.boxplot(list(data[cols].values.T))
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
ax.grid(grid)
ret = bp
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9, wspace=0.2)
return ret
def boxplot(data,
column=None,
by=None,
ax=None,
fontsize=None,
rot=0,
grid=True,
figsize=None):
"""
Make a box plot from DataFrame column optionally grouped b ysome columns or
other inputs
Parameters
----------
data : DataFrame or Series
column : column name or list of names, or vector
Can be any valid input to groupby
by : string or sequence
Column in the DataFrame to group by
fontsize : int or string
Returns
-------
ax : matplotlib.axes.AxesSubplot
"""
from pandas import Series, DataFrame
if isinstance(data, Series):
data = DataFrame({'x': data})
column = 'x'
def plot_group(grouped, ax):
keys, values = zip(*grouped)
keys = [_stringify(x) for x in keys]
ax.boxplot(values)
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
if column == None:
columns = None
else:
if isinstance(column, (list, tuple)):
columns = column
else:
columns = [column]
if by is not None:
if not isinstance(by, (list, tuple)):
by = [by]
fig, axes = _grouped_plot_by_column(plot_group,
data,
columns=columns,
by=by,
grid=grid,
figsize=figsize)
# Return axes in multiplot case, maybe revisit later # 985
ret = axes
else:
if ax is None:
ax = _gca()
fig = ax.get_figure()
data = data._get_numeric_data()
if columns:
cols = columns
else:
cols = data.columns
keys = [_stringify(x) for x in cols]
# Return boxplot dict in single plot case
bp = ax.boxplot(list(data[cols].values.T))
ax.set_xticklabels(keys, rotation=rot, fontsize=fontsize)
ax.grid(grid)
ret = bp
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9, wspace=0.2)
return ret
