py连接MySQL和pandas的学习.zip

#__*_ encoding: utf-8 --*- import os import numpy as np import pandas as pd import pandas_datareader.data as web import datetime ''' pd.read_csv test ''' # # ss(上海证券) sz(深圳证券) # df_csvave = web.DataReader('601233.ss',"yahoo",datetime.datetime(2018,1,1)) # print(df_csvave) # print(df_csvave.index) # print(df_csvave.columns) # # # 存数据 # path=os.getcwd() # df_csvave.to_csv(path+'/yahoo.csv',columns=df_csvave.columns,index=True) # 读数据 path=os.getcwd() df_csvload=pd.read_csv(path+'/yahoo.csv',parse_dates=True,index_col=0,encoding='gb2312') # 股票数据内容概况查看：head(),tail(),shape,describe(),info() # 前3行 print(df_csvload.head(3)) # 倒数3行 print(df_csvload.tail(3)) print(df_csvload.index) print(df_csvload.columns) print(df_csvload.shape) print(df_csvload.describe()) print(df_csvload.info()) # 缺失值处理方法：isnull(),notnull(),dropna(),fillna() print(df_csvload.isnull()) print(df_csvload[df_csvload.isnull().T.any()]) # 数据精度处理：round(),astype(),applymap(),lambda() # '%0.2f%'x (保留2位小数浮点型) df_csvload=df_csvload.applymap(lambda x:'%0.2f'%x) df_csvload.Volume=df_csvload.loc[:,['Volume']].apply(lambda x:'%0.0f'%x,axis=1) df_csvload.Volume=df_csvload.Volume.astype(int) print(df_csvload.head(4))