[实操]Python财务数据分析可视化

from matplotlib import pyplot as plt
plt.rcParams['font.family'] = 'Noto Sans CJK JP'
plt.rcParams['axes.unicode_minus'] = False
plt.figure()
plt.subplot(1,1,1)
x=[0,1,2,3,4]
y=[3,7,5,9,4]
plt.ylabel('Y_LABEL')
plt.xlabel('X_LABEL')
plt.title('Matlib_案例')
plt.plot(x,y)
plt.show()

import pandas as pd
df1 = pd.read_excel(r'./fin_databak.xlsx',sheet_name=0,converters={'年':str,'公司':str})
monthdict={'Jan':'01','Feb':'02','Mar':'03','Apr':'04','May':'05','Jun':'06','Jul':'07','Aug':'08','Sep':'09','Oct':'10','Nov':'11','Dec':'12'}
df1 = df1.drop('月2',axis=1,errors='ignore')
df1.insert(2,'月2',value=df1['月'].map(lambda x:monthdict[x]))
df2 = df1.sort_values(by=['公司','年','月2'],ascending=True).reset_index(drop=True)
df3 = pd.read_excel(r'./fin_databak.xlsx',sheet_name=1,converters={'年':str,'公司':str})
df4 = pd.merge(df2,df3,how='left')
df6 = df4.groupby(['年','月2','月'],as_index=False).sum()
df6.head(12)

 

df6['毛利率'] = (df6['营业收入']-df6['营业成本'])/df6['营业收入']
df6['利润率'] = df6['利润总额']/df6['营业收入']
df6['净利率'] = df6['净 利 润']/df6['营业收入']
df6['资产净利率'] = df6['净 利 润']/df6['资产合计']
df6['权益净利率'] = df6['净 利 润']/df6['权益合计']
df6['资产负载率'] = df6['负债合计']/df6['资产合计']
df6['平均单价'] = df6['营业收入']/df6['销售量']
df7 = df6.loc[(df6['年']=='2018'),['年','月','毛利率','利润率','净利率','资产净利率','权益净利率','平均单价']]
df7

df7.plot(x='月',y=['毛利率','利润率','净利率','资产净利率','权益净利率'],title='2018年公司个指利率统计',figsize=(12,4))

 

df7.plot('月',['平均单价','毛利率'],secondary_y=['毛利率'],kind='bar',title='2018年平均单价&毛利率对比',figsize=(12,4),rot=0)

figure,axes = plt.subplots(2,1,figsize=(12,8),sharex=True)
ax0 = df7.plot('月',['毛利率','利润率','净利率','资产净利率','权益净利率'],title='2018年平均单价&毛利率对比',ax=axes[0])
ax1 = df7.plot('月','平均单价',kind='bar',title='2018平均单价&毛利率比对',color='gold',ax=axes[1])
ax2 = df7.plot('月','毛利率',secondary_y=True,color='orangered',ax=axes[1],style='--',marker='o',linewidth=2)

from pyecharts.charts import Bar
from pyecharts import options as opts

bar = (
    Bar()
    .add_xaxis(['A公司','B公司','C公司','D公司','E公司','F公司'])
    .add_yaxis('库存量',[100,200,360,100,750,900])
)
bar.render_notebook

 

from pyecharts.globals import ThemeType
bar = (
    Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
    .add_xaxis(['A公司','B公司','C公司','D公司','E公司','F公司'])
    .add_yaxis('库存量',[100,200,360,100,750,900])
    .add_yaxis('销量',[100,200,160,100,650,200])
    .set_global_opts(title_opts=opts.TitleOpts(title='主标题:各公司库存量对比',subtitle='副标题:2019年'))
)
bar.render_notebook()

from pyecharts.charts import Line


y1 = df7['毛利率'].tolist()
y2 = df7['利润率'].tolist()
y3 = df7['净利率'].tolist()
y4 = df7['资产净利率'].tolist()
y5 = df7['权益净利率'].tolist()
x = df7['月'].tolist()

line = (
    Line(init_opts=opts.InitOpts(theme=ThemeType.DARK))
    .add_xaxis(x)
    .add_yaxis('毛利率',y1,linestyle_opts=opts.LineStyleOpts(width=3))
    .add_yaxis('利润率',y2,linestyle_opts=opts.LineStyleOpts(width=3))
    .add_yaxis('净利率',y3,linestyle_opts=opts.LineStyleOpts(width=3))
    .add_yaxis('资产净利率',y4,linestyle_opts=opts.LineStyleOpts(width=3))
    .add_yaxis('权益净利率',y5,linestyle_opts=opts.LineStyleOpts(width=3))
    .set_global_opts(title_opts=opts.TitleOpts(title='2018年公司各指标利率统计',
                    pos_left='center'),legend_opts=opts.LegendOpts(pos_top='5%'),
                    toolbox_opts=opts.ToolboxOpts(pos_top='%5'))
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
)
line.render_notebook()