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
- Go随机数的使用
随机数使用比较广泛,例如,抽奖.均衡等等. 下面简单说明其使用方法. Example1 package main import ( "log" "math/rand&qu ...
- Robots.txt 编写
搜索引擎Robots协议,是放置在网站根目录下robots.txt文本文件,在文件中可以设定搜索引擎蜘蛛爬行规则.设置搜索引擎蜘蛛Spider抓取内容规则.下面Seoer惜缘举例robots写法规则与 ...
- BASIC-4_蓝桥杯_数列特征
示例代码: #include <stdio.h>#include <stdlib.h> int main(void){ int n = 0 ; int i = 0 , max ...
- MYSQL ERROR 1045 (28000): Access denied for user (using password: YES)解决方案详细说明
1.首先这个问题出现的原因不详,可能是mysql的bug吧 2 解决步骤 1.首先停下mysql的服务 作者系统下命令为 /etc/init.d/mysqld stop 具体的停 ...
- Django自带的用户认证
1. 创建超级用户 python manage.py createsuperuser 2. 认证 校验用户名和密码 obj = auth.authenticate(request,user ...
- 经典算法 Manacher算法详解
内容: 1.原始问题 =>O(N^2) 2.Manacher算法 =>O(N) 1.原始问题 Manacher算法是由题目“求字符串中长回文子串的长度”而来.比如 abcdcb 的 ...
- sqlserver操作命令
启动命令:Net Start MSSqlServer 暂停命令:Net Pause MSSqlServer 重新启动暂停的命令:Net Continue MSSqlServer 停止命令:Net st ...
- javascript日期相减,求时间差
//计算时间差 var from_date = new Date(from_time); var end_date = new Date(end_time); var time_different = ...
- 内建函数(builtins)和functools
内建函数 Build-in Function,启动python解释器,输入dir(__builtins__), 可以看到很多python解释器启动后默认加载的属性和函数,这些函数称之为内建函数, 这些 ...
- UVA-10115
字符查找替换,WA了N次,一次只能替换一个,下一次find必须从第0个位置开始 import java.io.File; import java.io.FileNotFoundException; i ...