def census_1var(sheet,mp):
"""Parse census data using 1 variable. The DataFrame should be organised with:
FIRST ROW: should have the variable to classify dwellings
ColumnA should contain the region ID
ColumnB should contain the name of the region
"""
# Create a DataFrame with [id, name_region, Taxonomy, # of dwellings]
info = pd.DataFrame(columns=('id', 'Region', 'Taxonomy', 'Dwellings'))
# Iterate over first column (ragion_name)
for row in range(len(sheet)):
id_region = sheet.iloc[row][0]
name_region = sheet.iloc[row][1]
print 'Region ', id_region, " --> ", name_region
# Iterate over the row variables
for col, var in enumerate(sheet.columns[2:]):
# Check if the variable is present in the mapping scheme
if (functions.contain(mp.var1, var) == 'Correct'):
dwellings = sheet[var][row]
# print (''' {} dwellings with {}''').format(dwellings, var)
values = functions.mapping(var, '', '', mp, num_variables='one')
info = functions.info_append(info, values, id_region, name_region, dwellings)
elif var == 'Total':
print '---End of the region {} ---'.format(name_region)
continue
else:
print '.'
continue
return info
def census_2var(sheet,mp):
"""Parse census data using 2 variables.
The DataFrame should be organised with:
var1: in the rows (e.g. floor material)
var2: in the column [columnA] (e.g. wall material)
The name of the region should be placed in ColumnB and
ColumnA should contain the region ID starting with 'AREA # '.
"""
col0 = sheet[0] #column with VARIABLE_2
# Create a DataFrame with [id, name_region, Taxonomy, # of dwellings]
info = pd.DataFrame(columns=('id', 'Region', 'Taxonomy', 'Dwellings'))
name_region = 'Nacional'
id_region = 'AREA # 00'
for row_var2, variable2 in enumerate(col0):
# Identify the region
if str(variable2).find('AREA') != -1:
name_region = sheet.iloc[row_var2, 1]
id_region = col0[row_var2]
print "Region ", id_region, " --> ", name_region
continue
# Check if the variable2 is present in the mapping scheme
if (functions.contain(mp.var2, variable2) == 'Correct') & (name_region != 'RESUMEN'):
# print row_var2, "-->", variable2
# Iterate over the possible variable1
for column in range(1,len(sheet.columns) - 1): #to delete the last column with 'total'to match mp.var1
variable1 = mp.var1[column]
if variable1 == 'Total':
# print '''--- End of the variable1'''
break
# print column, '-->', variable1
dwellings = sheet.iloc[row_var2, column]
# print ('''There are {} dwellings with:
# var1: {}
# var2: {}''').format(dwellings,variable1, variable2)
values = functions.mapping(variable1, variable2, '', mp, num_variables='two')
info = functions.info_append(info, values, id_region, name_region, dwellings)
# print values
# print info
elif variable2 == 'Total':
# print '---End of the region {} ---'.format(name_region)
continue
elif variable2 == 'RESUMEN':
# print '-----END-----'
break
else:
# print '.'
continue
return info
def census_3var(sheet, mp):
"""Parse census data using 3 variables.
The DataFrame should be organised with:
var1: in the rows (e.g. floor material)
var2: in the first column [columnA] (e.g. wall material)
var3: in the second column [columnB] (e.g. type of dwelling)
The name of the region should be placed in ColumnB and
ColumnA should contain the region ID starting with 'AREA # '
"""
col0 = sheet[0] #column with VARIABLE_2
col1 = sheet[1] #column with VARIABLE_3
# Create a DataFrame with [id, name_region, Taxonomy, # of dwellings]
info = pd.DataFrame(columns=('id', 'Region', 'Taxonomy', 'Dwellings'))
name_region = 'Nacional'
id_region = 'AREA # 00'
for row_var2, variable2 in enumerate(col0):
# Identify the region
if str(variable2).find('AREA') != -1:
name_region = col1[row_var2]
id_region = col0[row_var2]
print "Region ", id_region, " --> ", name_region
continue
elif variable2 == 'RESUMEN':
name_region = 'RESUMEN'
continue
# Check if the variable2 is present in the mapping scheme
if (functions.contain(mp.var2, variable2) == 'Correct') & (name_region != 'RESUMEN'):
# print row_var2, "-->", variable2
# Iterate over variable1 (rows, e.g. floor material)
for column in range(2,len(sheet.columns)):
variable1 = sheet.iloc[row_var2, column]
if variable1 == 'Total':
# print '''--- End of the variable1'''
break
# print column, '-->', variable1
# Iterate over variable3 (2nd column, e.g. house type)
i = 1
while True:
variable3 = col1[row_var2 + i]
# print str(row_var2 + i),'-->', variable3
if variable3.find('Total') != -1:
# print '''--- End of the variable3'''
break
else:
dwellings = sheet.iloc[row_var2 + i, column]
# print ('''There are {} dwellings with:
# var1: {}
# var2: {}
# var3: {}''').format(dwellings, variable1, variable2, variable3)
values = functions.mapping(variable1, variable2, variable3, mp, num_variables='three')
info = functions.info_append(info, values, id_region, name_region, dwellings)
i += 1
# print values
# print info
elif variable2 == 'Total':
# print '---End of the region {} ---'.format(name_region)
continue
else:
# print '.'
continue
return info