pandas数据分析练习

       # coding=utf-8
       """
        @Project ：pachong-master
        @File ：list_series.py
        @Author ：gaojs
        @Date ：2022/6/5 22:06
        @Blogs : https://www.gaojs.com.cn
       """
       import pandas as pd
       import numpy as np
       class Pandas:
          """
        pandas类库练习
        """
          def __init__(self):
              pass
          def list_series(self):
              """
        列表转换成series:索引为数字
        :return:
        """
               course = ["语文", "数学", "英语", "计算机"]
               data = pd.Series(data=course)
              print(data)
          def dict_series(self):
              """
        字典转换成series：索引为key值
        :return:
        """
               grades = {"语文": 80, "数学": 90, "英语": 100, "计算机": 95}
               data = pd.Series(data=grades)
              print(data)
          def series_list(self):
              """
        series转换成list
        :return:
        """
               grades = {"语文": 80, "数学": 90, "英语": 100, "计算机": 95}
               data = pd.Series(data=grades)
               members = data.to_list()
              print(members)
          def series_dataframe(self):
              """
        series转换成dataframe
        :return:
        """
               grades = {"语文": 80, "数学": 90, "英语": 100, "计算机": 95}
               data = pd.Series(data=grades)
               df = pd.DataFrame(data, columns=['grade'])
              print(df)
          def numpy_create_series(self):
              """
        numpy创建series
        :return:
        """
               s = pd.Series(
                  # 树脂：10-90，间隔10
                   np.arange(10, 100, 10),
                  # 索引：101-109，间隔1
                   index=np.arange(101, 110),
                  # 类型：float64
                   dtype='float'
               )
              print(s)
          def series_datatype(self):
              """
        数据类型转换
        :return:
        """
               s = pd.Series(
                   data=["001", "002", "003", "004"],
                   index=list("abcd")
               )
              # s = s.astype(int)
              # 效果一样,map里的int是函数
               s = s.map(int)
              print(s)
          def series_add_ele(self):
              """
        给series添加新元素
        :return:
        """
               grades = {"语文": 80, "数学": 90, "英语": 100, "计算机": 95}
               data = pd.Series(data=grades)
               data = data.append(pd.Series({
                  "物理": 99,
                  "高数": 88
               }))
              print(data)
          def series_to_dataframe(self):
              """
        series转换成dataframe
        :return:
        """
               grades = {"语文": 80, "数学": 90, "英语": 100, "计算机": 95}
               data = pd.Series(data=grades)
               df = data.reset_index()
               df.columns = ['course', 'grade']
              print(df)
          def dict_create_dataframe(self):
              """
        使用字典创建dataframe
        :return:
        """
               df = pd.DataFrame(
                   {
                      "姓名": ["张三", "李四", "王麻子", "高先生"],
                      "性别": ["男", "女", "男", "女"],
                      "年龄": [18, 19, 20, 21]
                   }
               )
              print(df)
          def set_dataframe_index(self):
              """
        给dataframe设置索引列
        :return:
        """
               df = pd.DataFrame(
                   {
                      "姓名": ["张三", "李四", "王麻子", "高先生"],
                      "性别": ["男", "女", "男", "女"],
                      "年龄": [18, 19, 20, 21]
                   }
               )
               df.set_index("姓名", inplace=True)
              print(df)
          def dataMonth(self):
              """
        一个月份所有日期
        :return:
        """
              # date_range = pd.date_range(start='2022-05-01', end='2022-05-31')
               date_range = pd.date_range(start='2022-05-01', periods=31)
              print(date_range)
          def mondayDate(self):
              """
        一年所有的周一日期
        :return:
        """
              # data_range = pd.date_range(start='2022-01-01', end='2022-12-31', freq='W-Mon')
               data_range = pd.date_range(start='2022-01-01', periods=52, freq='W-Mon')
              print(data_range)
          def dayHourDate(self):
              """
        一日所有的小时
        :return:
        """
              # data_range = pd.date_range(start='2022-01-01', periods=24, freq='H')
               data_range = pd.date_range(start='2022-01-01', end='2022-01-02', freq='H', closed='left')
              print(data_range)
          def dateToDataframe(self):
              """
        日期生成DataFrame
        :return:
        """
               data_range = pd.date_range(start='2022-5-01', periods=31, freq='D')
              # print(data_range)
               df = pd.DataFrame(data=data_range, columns=['day'])
               df['day_of_year'] = df['day'].dt.dayofyear
              print(df)
          def dateToRandomDataFrame(self):
              """
        日期随机生成dataframe:均匀 正态 二项分布
        :return:
        """
               data_range = pd.date_range(start='2022-1-01', periods=1000, freq='D')
               data = {
                  'norm': np.random.normal(loc=0, scale=1, size=1000),
                  'unifom': np.random.uniform(low=0, high=1, size=1000),
                  'binomial': np.random.binomial(n=1, p=0.2, size=1000)
               }
               df = pd.DataFrame(data=data, index=data_range)
              print(df)
          def logHeadLine(self):
              """
        打印前10行
        :return:
        """
               data_range = pd.date_range(start='2022-1-01', periods=1000, freq='D')
               data = {
                  'norm': np.random.normal(loc=0, scale=1, size=1000),
                  'unifom': np.random.uniform(low=0, high=1, size=1000),
                  'binomial': np.random.binomial(n=1, p=0.2, size=1000)
               }
               df = pd.DataFrame(data=data, index=data_range)
              print(df.head(10))
              print(df.tail(5))
          def catDataFrame(self):
              """
        查看dataframe基本信息
        :return:
        """
               data_range = pd.date_range(start='2022-1-01', periods=1000, freq='D')
               data = {
                  'norm': np.random.normal(loc=0, scale=1, size=1000),
                  'unifom': np.random.uniform(low=0, high=1, size=1000),
                  'binomial': np.random.binomial(n=1, p=0.2, size=1000)
               }
               df = pd.DataFrame(data=data, index=data_range)
              print(df.info())
              print(df.describe())
          def countDataAppear(self):
              """
        统计数据出现次数
        :return:
        """
               data_range = pd.date_range(start='2022-1-01', periods=1000, freq='D')
               data = {
                  'norm': np.random.normal(loc=0, scale=1, size=1000),
                  'unifom': np.random.uniform(low=0, high=1, size=1000),
                  'binomial': np.random.binomial(n=1, p=0.2, size=1000)
               }
               df = pd.DataFrame(data=data, index=data_range)
              print(df['binomial'].value_counts())
          def saveCSV(self):
              """
        保存前一百行存入csv
        :return:
        """
               data_range = pd.date_range(start='2022-1-01', periods=1000, freq='D')
               data = {
                  'norm': np.random.normal(loc=0, scale=1, size=1000),
                  'unifom': np.random.uniform(low=0, high=1, size=1000),
                  'binomial': np.random.binomial(n=1, p=0.2, size=1000)
               }
               df = pd.DataFrame(data=data, index=data_range)
               df.head(10).to_csv('分布数据前50.csv')
          def csvLoadDataframe(self):
              """
        csv加载成dataframe
        :return:
        """
               df = pd.read_csv('分布数据前50.csv', index_col=0)
              print(df.info())
              print(df.head())
       # test = Pandas()
       # test.csvLoadDataframe()
   
  

   
  
  

未完待续