吴裕雄 python 数据处理(1)
import time
print(time.time())
print(time.localtime())
print(time.strftime('%Y-%m-%d %X',time.localtime()))
绘图显示中文配置
import matplotlib.pyplot as plt
a = [1,1,2,3]
b = [2,2,2,2]
plt.plot(a,b)
plt.title("天生自然")
plt.show()
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv")
print(df.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
df.to_csv("E:\\temp\\taobao_price_data.csv", columns=["宝贝","价格"],index=False,header=True)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df[0:3])
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
cols = df[["宝贝","价格"]]
print(cols.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.ix[0:3,["宝贝","价格"]]
print(a)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
df["销售量"] = df["价格"]*df["成交量"]
print(df.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[(df["价格"]<100)&(df["成交量"]<10000)]
print(a)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df.head())
df1 = df.set_index("位置")
print(df1.head())
df2 = df1.sort_index()
print(df2.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
df1 = df.set_index(["位置","卖家"])
print(df1.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
df1 = df.set_index(["位置","卖家"]).sortlevel(0)
print(df1.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.drop(["宝贝","卖家"],axis=1)
print(a.head())
b = df.drop(["宝贝","卖家"],axis=1).groupby("位置")
print(b.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.drop(["宝贝","卖家"],axis=1).groupby("位置").mean()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.drop(["宝贝","卖家"],axis=1).groupby("位置").mean().sort_values("成交量",ascending=False)
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.drop(["宝贝","卖家"],axis=1).groupby("位置").sum().sort_values("成交量",ascending=False)
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df.info())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df.describe())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
print(df.describe(include=["object"]))
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df["成交量"].groupby(df["位置"])
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df["成交量"].groupby(df["位置"]).mean()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df["成交量"].groupby([df["位置"],df["卖家"]]).mean()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.groupby("位置").mean()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.groupby(["位置","卖家"]).mean()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df.groupby(["位置","卖家"]).size()
print(a.head())
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[30:35][["位置","卖家"]]
print(a)
b = df[90:95][["卖家","成交量"]]
print(b)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[30:35][["位置","卖家"]]
b = df[30:35][["卖家","成交量"]]
c = pd.merge(a,b)
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[30:35][["位置","卖家"]]
b = df[30:35][["卖家","成交量"]]
c = pd.merge(a,b,on="卖家")
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[10:20][["位置","卖家"]]
b = df[30:40][["卖家","成交量"]]
c = pd.merge(a,b,how="outer")
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[10:20][["位置","卖家"]]
b = df[30:40][["卖家","成交量"]]
c = pd.merge(a,b,how="left")
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[10:20][["位置","卖家"]]
b = df[30:40][["卖家","成交量"]]
c = pd.merge(a,b,how="right")
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:10][["位置","卖家"]]
print(a)
b = df[:10][["卖家","成交量"]]
print(b)
c = pd.merge(a,b,how="right")
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:10][["位置","卖家"]]
b = df[:10][["卖家","成交量"]]
c = pd.merge(a,b,left_index=True,right_index=True)
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:10][["位置","卖家"]]
b = df[:10][["价格","成交量"]]
c = pd.merge(a,b,left_index=True,right_index=True)
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:10][["位置","卖家"]]
b = df[:10][["价格","成交量"]]
c = a.join(b)
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:5]["宝贝"]
b = df[5:10]["宝贝"]
c = df[10:15]["宝贝"]
d = pd.concat([a,b,c])
print(d)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:5]["宝贝"]
print(a)
b = df[:5]["价格"]
print(b)
c = df[:5]["成交量"]
print(c)
d = pd.concat([a,b,c],axis=1)
print(d)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:5][["位置","卖家"]]
print(a)
b = df[:5][["价格","成交量"]]
print(b)
c = pd.concat([a,b])
print(c)
import pandas as pd
df = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\taobao_data.csv",delimiter=",",encoding="utf8",header=0)
a = df[:5][["位置","卖家"]]
print(a)
b = df[:5][["价格","成交量"]]
print(b)
c = pd.concat([a,b],axis=1)
print(c)
吴裕雄 python 数据处理(1)的更多相关文章
- 吴裕雄 python 数据处理(3)
import time a = time.time()print(a)b = time.localtime()print(b)c = time.strftime("%Y-%m-%d %X&q ...
- 吴裕雄 python 数据处理(2)
import pandas as pd data = pd.read_csv("F:\\python3_pachongAndDatareduce\\data\\pandas data\\hz ...
- 吴裕雄 python 神经网络——TensorFlow 输入数据处理框架
import tensorflow as tf files = tf.train.match_filenames_once("E:\\MNIST_data\\output.tfrecords ...
- 吴裕雄 python神经网络 花朵图片识别(10)
import osimport numpy as npimport matplotlib.pyplot as pltfrom PIL import Image, ImageChopsfrom skim ...
- 吴裕雄 python神经网络 花朵图片识别(9)
import osimport numpy as npimport matplotlib.pyplot as pltfrom PIL import Image, ImageChopsfrom skim ...
- 吴裕雄 python 神经网络——TensorFlow pb文件保存方法
import tensorflow as tf from tensorflow.python.framework import graph_util v1 = tf.Variable(tf.const ...
- 吴裕雄 python 神经网络——TensorFlow 花瓣分类与迁移学习(4)
# -*- coding: utf-8 -*- import glob import os.path import numpy as np import tensorflow as tf from t ...
- 吴裕雄 python 神经网络——TensorFlow 花瓣分类与迁移学习(3)
import glob import os.path import numpy as np import tensorflow as tf from tensorflow.python.platfor ...
- 吴裕雄 python 神经网络——TensorFlow 花瓣分类与迁移学习(2)
import glob import os.path import numpy as np import tensorflow as tf from tensorflow.python.platfor ...
随机推荐
- HttpPostedFile类
在研究HttpRequest的时候,搞文件上传的时候,经常碰到返回HttpPostedFile对象的情况,这个对象才是真正包含文件内容的东西. 经常要获取的最重要的内容是FileName属性与Sava ...
- WebClient类
WebClient类提供向 URI 标识的资源发送数据和从 URI 标识的资源接收数据的公共方法. 其实就相当于创建一个请求客户端.可以获取网页和各种各样的信息,包括交互. 通过MSDN来看看WebC ...
- module.exports用法
module.exports 对象是由模块系统创建的.在我们自己写模块的时候,需要在模块最后写好模块接口,声明这个模块对外暴漏声明内容,module.exports提供了暴漏接口的方法. 1.返回一个 ...
- windows server 2008 R2 无法启用"网络发现" 需要启动的服务
必须打开以下服务: 1.dnscache(简写.fdrespub(简写) 2.SSDP Discovery 3. UPnP Device Host 4. Computer Browser 5.Serv ...
- python处理excel(二):写
代码参考自zhoujie.函数接口可参考该blog. 基本的write函数接口很简单: 新建一个excel文件 file = xlwt.Workbook() (注意这里的Workbook首字母是大写) ...
- 学习笔记之Kubernetes
Kubernetes | Production-Grade Container Orchestration https://kubernetes.io/ Kubernetes is an open-s ...
- [转]预编译 ASP.NET 网站
转自:如何:预编译 ASP.NET 网站 Visual Studio 2005 预编译 ASP.NET 网站可缩短用户的初始响应时间,因为页在第一次被请求时无需编译.这对于经常更新的大型网站尤其有 ...
- dede:channel的type改为son,currentstyle当前样式就不起作用
我在修改得闲佬设计作品展示列表页的时候,遇到一个问题,就是channel的type改为son时,currentstyle属性不起作用,试了好久都没办法,后来上网找资料,就找到了解决方法,记录一下. ...
- Linux命令详解-Apache网站服务器配置和管理
1.Apache网站服务器配置和管理 1.源码包安装 2.rpm包安装 rpm –a | grep httpd 3.启动服务 service httpd start 4.配置文件: /etc/http ...
- ETL,BPM与ESB三者的一些感悟
1.ETL: 数据层之间,主要在数据库层面上进行数据抽取过程------数据库层 2.ESB 异构系统之间通过总线技术,实现系统交互---------------系统通信层 3.BPM 自动化流程处理 ...