def delta_s(X_c, X, style, level, kind, title, ranshow, title_font, figsize,
directory, fig_format, color, indicator, detail, indeces, ex_save,
Units):
'''
Parameters
----------
As described in the main class
Returns
-------
Nothing specific. But it shows the plot, save the plots and save the plotted
data in form of excel file
'''
# As some processes are needed to be done on the inputs, to keep the main variable unchanged, we will make a copy of them
X_c = X_c.copy() # After shock
X = X.copy() # Baseline
# Checking the styles,units,levels and the indicator
style = style_check(style)
tit, level = level_check(level)
kind = kind_check(kind)
# To check if the given indicator exists in the database aggregated level
indicator = indic_check(indicator,
list(indeces['S_ind'].get_level_values(1)))
# Implementing the plot style
plt.style.use(style)
if detail:
# For the detailed case, more levels should be taken to show detailed information
X_c = X_c.loc[(slice(None), indicator),
level].groupby(axis=1,
level=[0,
2]).sum().groupby(axis=0,
level=0).sum()
X = X.loc[(slice(None), indicator),
level].groupby(axis=1,
level=[0, 2]).sum().groupby(axis=0,
level=0).sum()
else:
# Otherwise, only the main level will be taken
X_c = X_c.loc[indicator, level]
X = X.loc[indicator, level]
# defining the d_x matrix
if kind == 'Absolute':
# Here the unit won't be printed because there is not a single unit anymore
d_x, unit = (X_c - X), Units.loc[indicator].iloc[0].values.tolist()[0]
else:
d_x, unit = (X_c - X) / X * 100, '%'
# if detail is True, we need to reindex it
if detail:
# Take only the first level of index
d_x.index = d_x.index.get_level_values(0)
d_x.columns = d_x.columns.get_level_values(1)
# Due to competutional errors, even in the case that one thing is not changed,
# we may have very small differences
# This makes the graphs ugly!! To solve the issue we print an error for the
# user to make them understand.
if abs(d_x.sum().sum()) <= 0.000001:
print(
'The following matrix seems to be unchanged in the implemented shock, Maybe the changes are very small or they are related to computational errors.'
)
# Specifing the range of showing results
d_x = drop_fun(data=d_x, ranshow=ranshow)
# Transposing the dataframe
d_x = d_x.T
# Removing the name of the indeces for better representation
d_x.index.name = None
d_x.columns.name = None
# Title Definition
# If is not given by user, choose the default title
if title == 'default':
title = '{} Change{}'.format(indicator, tit)
# Otherwise, use the one which is given by user.
else:
title = title
# If detail is True, we need legens
if detail:
try:
d_x.plot(kind='bar', stacked=True,
colormap=color) # With a color map
except:
d_x.plot(kind='bar', stacked=True,
color=color) # With a color list
plt.legend(loc='center left',
bbox_to_anchor=(1, 0.5),
fancybox=True,
shadow=True)
# Otherwise, we don't need to have legends, becuase ther is only one
else:
try:
d_x.plot(kind='bar', stacked=False, legend=False, colormap=color)
except:
d_x.plot(kind='bar', stacked=False, legend=False, color=color)
plt.title(title)
plt.ylabel(unit)
# Saving and showing the plot
# check if the same file already exists or not
i = 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
plt.savefig(dir, bbox_inches='tight', dpi=150)
plt.show()
# Saving the final dataframe into an excel file in the same directory
i = 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
if ex_save:
with pd.ExcelWriter(dir) as writer:
d_x.to_excel(writer)
def delta_p(X_c, X, style, level, title, title_font, figsize, directory,
fig_format, color, ex_save):
'''
Parameters
----------
As described in the main class
Returns
-------
Nothing specific. But it shows the plot, save the plots and save the plotted
data in form of excel file
'''
# As some processes are needed to be done on the inputs, to keep the main variable unchanged, we will make a copy of them
X_c = X_c.copy() # After shock
X = X.copy() # Baseline
# Checking the styles,title and the unit
style = style_check(style)
tit, level = level_check(level)
# Implementing the plot style
plt.style.use(style)
# Taking the level only from the columns
X_c = X_c[level]
X = X[level]
# Title Definition
# The title not given by the user
if title == 'default':
title = 'Price ratio{}'.format(tit)
# Title given by the user
else:
title = title
# Making the d_x matrix: Here is X_c/X cause is the price ratio
d_x = X_c / X
# Reindexing the index and columns:
# If both level exist
if len(level) == 2:
d_x.index, d_x.columns = X.index.get_level_values(0), [
d_x.columns.get_level_values(0),
d_x.columns.get_level_values(1)
]
# If only one level exits: This makes the plot more beautiful!!
else:
d_x.index, d_x.columns = X.index.get_level_values(
0), d_x.columns.get_level_values(1)
# Removing the name of the indeces for better representation
d_x.index.name = None
d_x.columns.name = None
# Using a heatmap plot
fig = plt.figure(figsize=figsize)
ax = sns.heatmap(d_x.T, annot=False, cmap=color)
plt.ylabel('Price Ratio')
plt.title(title)
# Save and show the plot
i = 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
plt.savefig(dir, bbox_inches='tight', dpi=150)
plt.show()
# save the final dataframe in form of an excel file in the same directory
i = 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
if ex_save:
with pd.ExcelWriter(dir) as writer:
d_x.to_excel(writer)
def delta_xv(X_c, X, style, unit, m_unit, level, kind, title, ranshow,
title_font, figsize, directory, fig_format, color, info, drop,
ex_save):
'''
Parameters
----------
As described in the main class
Returns
-------
Nothing specific. But it shows the plot, save the plots and save the plotted
data in form of excel file
'''
# As some processes are needed to be done on the inputs, to keep the main variable unchanged, we will make a copy of them
X_c = X_c.copy() # After shock
X = X.copy() # Baseline
# default unit
if unit == 'default':
unit = m_unit
# Checking the units and styles
unit = unit_check(unit)
style = style_check(style)
conversion = unit_converter(m_unit, unit)
tit, level = level_check(level)
kind = kind_check(kind)
# Implementing the plot style
plt.style.use(style)
# Reshaping X matrix for better representation and Taking the level
if info == 'X':
# If the plot is X, it should be reshaped
X_c = x_reshape(X_c)
X = x_reshape(X)
# With the new reshaped X, the levels should be taken from both
# index and columns side
X_c = X_c.loc[level, level]
X = X.loc[level, level]
elif info == 'VA':
# In case of VA, the level should be taken from the columns not the index
X_c = X_c[level]
X = X[level]
# defining the d_x matrix
# For absolute case, d_x is the differnece between the shock and baseline
# results multiplied with the conversion ratio. Unit as given by user
# For percentage case, d_x is the relative change of production with respect
# to the baseline. Unit is %
if kind == 'Absolute': d_x = (X_c - X) * conversion
else: d_x, unit = (X_c - X) / X * 100, '%'
# Check the title
if info == 'X':
# If the title is not given by the user, the default one will be used
if title == 'default':
title = 'Production Change{}'.format(tit)
# Otherwise, the one given by the user will be used
else:
title = title
elif info == 'VA':
# If the title is not given by the user, the default one will be used
if title == 'default':
title = 'Value Added Change{}'.format(tit)
# Otherwise, the one given by the user will be used
else:
title = title
# Reindexing to avoid showing multiple indeces: only the second level
if info == 'X': d_x.index = X.index.get_level_values(1)
elif info == 'VA':
# If both levels are taken, the first two levels of columns will be taken
if len(level) == 2:
d_x.index, d_x.columns = X.index.get_level_values(0), [
d_x.columns.get_level_values(0),
d_x.columns.get_level_values(1)
]
# Otherwise, just the second level will be taken. This make the plots more beautiful
else:
d_x.index, d_x.columns = X.index.get_level_values(
0), d_x.columns.get_level_values(1)
# Droping some of the categories based on the user input
if drop:
d_x = d_x.drop(drop)
# defining the range of the valuse to be shown
if info == 'X': d_x = drop_fun(data=d_x.T, ranshow=ranshow)
elif info == 'VA': d_x = drop_fun(data=d_x, ranshow=ranshow)
# Transposing the dataframe
d_x = d_x.T
# Removing the name of the indeces for better representation
d_x.index.name = None
d_x.columns.name = None
# Plotting
if info == 'X':
# If both levels are given, we need to have legend cuase two categries exist
if len(level) == 2:
# Depending on the input of the color, the code will be different
try:
d_x.plot(kind='bar',
figsize=figsize,
stacked=True,
colormap=color) # colormap if a color map is given
except:
d_x.plot(kind='bar',
figsize=figsize,
stacked=True,
color=color) # color if a color list is given
plt.legend(loc='center left',
bbox_to_anchor=(1, 0.5),
fancybox=True,
shadow=True)
# If only one level exists, we dont need the legend anly more
else:
try:
d_x.plot(kind='bar',
figsize=figsize,
legend=None,
stacked=True,
colormap=color)
except:
d_x.plot(kind='bar',
figsize=figsize,
legend=None,
stacked=True,
color=color)
if info == 'VA':
try:
d_x.plot(kind='bar', figsize=figsize, stacked=True, colormap=color)
except:
d_x.plot(kind='bar', figsize=figsize, stacked=True, color=color)
plt.legend(loc='center left',
bbox_to_anchor=(1, 0.5),
fancybox=True,
shadow=True)
# Due to competutional errors, even in the case that one thing is not changed,
# we may have very small differences
# This makes the graphs ugly!! To solve the issue we print an error for the
# user to make them understand.
if abs(d_x.sum().sum()) <= 0.000001:
print(
'The following matrix seems to be unchanged in the implemented shock, Maybe the changes are very small or they are related to computational errors.'
)
# check if the same file already exists or not
i = 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.{}'.format(directory, title, i, fig_format)
plt.title(title, fontsize=title_font)
plt.ylabel(unit)
plt.savefig(dir, bbox_inches='tight', dpi=150)
plt.show()
# Save the dataframe into a excel file in the same directory
# Check if the excel file with the same name already exists
i = 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
while file_exist(dir):
i += 1
dir = '{}\{}_{}.xlsx'.format(directory, i, title)
if ex_save:
with pd.ExcelWriter(dir) as writer:
d_x.to_excel(writer)