pandas 制造数据和简单的画图

# 0 数据制造
import pandas as pd
df1 =pd.DataFrame(10*np.random.rand(7,3),index=["A","B","C","D","E","F","G"],columns=["ALL","Fail","PASS"])
df1=pd.DataFrame(np.arange(16).reshape((4,4)),index=['a','b','c','d'],columns=['one','two','three','four'])
# 2层索引
df1=pd.DataFrame(np.arange(16).reshape((4,4)),index=[['a','b','c','d'],['A','B','C','D']],columns=['one','two','three','four'])

df2 = pd.DataFrame({
    "pdate": ["2019-12-01", "2019-12-02", "2019-12-04", "2019-12-05"],
    "pv": [100, 200, 400, 500],
    "uv": [10, 20, 40, 50],
})

data = {'水果':['苹果','梨','草莓'],
       '数量':[3,2,5],
       '价格':[10,9,8]}
df3 = pd.DataFrame(data)


data = {'数量':{'苹果':3,'梨':2,'草莓':5},
       '价格':{'苹果':10,'梨':9,'草莓':8}}
df4 = pd.DataFrame(data)


df5= pd.DataFrame([[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]], \
columns=["col1", "col2", "col3", "col4"]) 


s1 = pd.Series(
    [
        "this is a regular sentence",
        "https://docs.python.org/3/tutorial/index.html",
        np.nan
    ])



# 1 简单的画图 pyecharts（pip install pyecharts）
from pyecharts.charts import Line
from pyecharts import options as opts

df=pd.DataFrame(10*np.random.rand(7,3),index=["A","B","C","D","E","F","G"],columns=["ALL","Fail","PASS"])

# 折线图
line = Line()
# x轴
line.add_xaxis(df.index.to_list())
# 每个y轴
line.add_yaxis("失败", df["Fail"].round(2).to_list())
line.add_yaxis("成功", df["PASS"].round(2).to_list())

# 图表配置
line.set_global_opts(
    title_opts=opts.TitleOpts(title="股票2019年"),
    tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross")
)
# 渲染数据
line.render_notebook()
line.render()




# 2 造数据和简单的画图 plot()
import pandas as pd
%matplotlib inline

df = pd.DataFrame({
    "pdate": ["2019-12-01", "2019-12-02", "2019-12-04", "2019-12-05"],
    "pv": [100, 200, 400, 500],
    "uv": [10, 20, 40, 50],
})

df.set_index("pdate").plot()


# 1
df1=pd.DataFrame(10*np.random.rand(7,3),index=["A","B","C","D","E","F","G"],columns=["ALL","Fail","PASS"])
df2=pd.DataFrame(10*np.random.rand(7,3),index=["A","B","C","D","E","F","G"],columns=["ALL","Fail","PASS"])

def prep_df(df, name):
    df = df.stack().reset_index()
    df.columns = ['c1', 'result', 'values']
    df['DF'] = name
    return df

df1 = prep_df(df1, 'DF1')
df2 = prep_df(df2, 'DF2')
df = pd.concat([df1, df2])



# 2
df = pd.read_csv('xxx.csv',encoding = "utf-8",delimiter=",",error_bad_lines=False)
df.set_index(pd.to_datetime(df["time"]),inplace=True)
source = df.sort_index()[['time','all case name','pass case','failed case']]
source = source.melt('time', var_name='category', value_name='y')


# 3
import pandas as pd
data = {'水果':['苹果','梨','草莓'],
       '数量':[3,2,5],
       '价格':[10,9,8]}
df = pd.DataFrame(data)
print(df)
print('*********')


data = {'数量':{'苹果':3,'梨':2,'草莓':5},
       '价格':{'苹果':10,'梨':9,'草莓':8}}
df = pd.DataFrame(data)
print(df)
print('*********')

data = {'水果':pd.Series(['苹果','梨','草莓']),
       '数量':pd.Series([3,2,5]),
       '价格':pd.Series([10,9,8])}
df = pd.DataFrame(data)
print(df)