def add_cpi_page(canvas_para, length):
"""
函数功能：增加CPI页
:param canvas_para:
:return:
"""
c = canvas_para
cpi_df = ts.get_cpi()
cpi_df['month'] = cpi_df.apply(lambda x: stdMonthDate(x['month']), axis=1)
cpi_df = cpi_df.sort_values(
by='month', ascending=False).head(length).sort_values(by='month',
ascending=True)
cpi = extract_point_from_df_date_x(df_origin=cpi_df,
date_col='month',
y_col='cpi',
timeAxis='month')
gdp_pull_drawing = gen_lp_drawing([tuple(cpi)],
data_note=['CPI增长率'],
time_axis='month')
renderPDF.draw(drawing=gdp_pull_drawing, canvas=c, x=10, y=letter[1] * 0.6)
c.showPage()
return c
def add_ppi_page(canvas_para, length):
"""
函数功能：工业品出厂价格指数
:param canvas_para:
:return:
"""
c = canvas_para
ppi_df = ts.get_ppi()
ppi_df['month'] = ppi_df.apply(lambda x:stdMonthDate(x['month']), axis=1)
ppi_df = ppi_df.sort_values(by='month',ascending=False).head(length).sort_values(by='month',ascending=True)
ppiip = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='ppiip', timeAxis='month')
ppi = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='ppi', timeAxis='month')
qm = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='qm', timeAxis='month')
rmi = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='rmi', timeAxis='month')
pi = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='pi', timeAxis='month')
ppi_industry_drawing = gen_lp_drawing([tuple(ppiip), tuple(ppi), tuple(qm), tuple(rmi), tuple(pi)],
data_note=['工业品出厂价格指数',
'生产资料价格指数',
'采掘工业价格指数',
'原材料工业价格指数',
'加工工业价格指数'],
time_axis='month')
renderPDF.draw(drawing=ppi_industry_drawing, canvas=c, x=10, y=letter[1] * 0.6)
cg = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='cg', timeAxis='month')
food = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='food', timeAxis='month')
clothing = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='clothing', timeAxis='month')
roeu = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='roeu', timeAxis='month')
dcg = extract_point_from_df_date_x(df_origin=ppi_df, date_col='month', y_col='dcg', timeAxis='month')
ppi_life_drawing = gen_lp_drawing([tuple(cg), tuple(food), tuple(clothing), tuple(roeu), tuple(dcg)],
data_note=['生活资料价格指数',
'食品类价格指数',
'衣着类价格指数',
'一般日用品价格指数',
'耐用消费品价格指数'],
time_axis='month')
renderPDF.draw(drawing=ppi_life_drawing, canvas=c, x=10, y=letter[1] * 0.2)
c.showPage()
return c
# encoding = utf-8
from Config.GlobalSetting import *
from SDK.AboutTimeSub import stdMonthDate
ppi_df = ts.get_ppi()
# trick to get the axes
fig, ax = plt.subplots()
std_date = list(map(lambda x: stdMonthDate(x), ppi_df['month']))
# plot data
ax.plot(std_date, ppi_df['ppiip'], 'go--', label=U'工业品出厂')
ax.plot(std_date, ppi_df['ppi'], 'b*--', label=U'生产资料')
ax.plot(std_date, ppi_df['qm'], 'cv--', label=U'采掘工业')
ax.plot(std_date, ppi_df['rmi'], 'g*--', label=U'原材料工业')
ax.plot(std_date, ppi_df['pi'], 'k*--', label=U'加工工业')
ax.plot(std_date, ppi_df['cg'], 'm*--', label=U'生活资料')
ax.plot(std_date, ppi_df['food'], 'r*--', label=U'食品类')
ax.plot(std_date, ppi_df['clothing'], 'y^-', label=U'衣着类')
ax.plot(std_date, ppi_df['roeu'], 'y*--', label=U'一般日用品')
ax.plot(std_date, ppi_df['dcg'], 'y*:', label=U'耐用消费品')
xticklabels = list(std_date)
xticklabels.reverse()
ax.set_xticklabels(xticklabels, rotation=90)
ax.set_title('各种价格指数')
ax.legend(loc='best')
plt.show()