随笔分类 -  python数据分析

摘要:#实战准备#股票市场分析实战--数据获取#https://finance.yahoo.com"""import pandas_datareader as pdralibaba = pdr.get_data_yahoo("BABA")#print(alibaba.head())# High Low O 阅读全文
posted @ 2019-07-04 10:45 nikecode 阅读(6674) 评论(0) 推荐(0)
摘要:"""import pandas as pdimport numpy as npfrom pandas import Series,DataFrameimport matplotlib.pyplot as pltimport seaborn as sns""""""#Seaborn 是matplot 阅读全文
posted @ 2019-07-04 10:44 nikecode 阅读(776) 评论(0) 推荐(0)
摘要:#38#Pandas绘图之Seriesimport pandas as pdimport numpy as npfrom pandas import Series,DataFrameimport matplotlib.pyplot as plt"""#cumsum()函数求和s = Series([ 阅读全文
posted @ 2019-07-04 10:43 nikecode 阅读(601) 评论(0) 推荐(0)
摘要:import pandas as pdimport numpy as npfrom pandas import Series,DataFrame"""df = pd.read_excel("sales-funnel.xlsx")#print(df)# Account Name ... Price S 阅读全文
posted @ 2019-07-04 10:42 nikecode 阅读(1118) 评论(0) 推荐(0)
摘要:import pandas as pdimport numpy as npfrom pandas import Series,DataFrame#时间序列的操作基础from datetime import datetime"""t = datetime(2016,9,10)print(t)#2016 阅读全文
posted @ 2019-07-04 10:40 nikecode 阅读(392) 评论(0) 推荐(0)
摘要:import pandas as pdimport numpy as npfrom pandas import Series,DataFrame#重命名DataFrame的indexdf1 = DataFrame(np.arange(9).reshape(3,3),index=["BJ","SH", 阅读全文
posted @ 2019-07-04 10:39 nikecode 阅读(275) 评论(0) 推荐(0)
摘要:import pandas as pdimport numpy as npfrom pandas import Series,DataFrame#df1 = DataFrame({'城市':["北京","上海","广州"],'人口':[1000,2000,1500]})# print(df1)# 城 阅读全文
posted @ 2019-07-04 10:38 nikecode 阅读(373) 评论(0) 推荐(0)
摘要:#NaN --means Not a Numberimport pandas as pdimport numpy as npfrom pandas import Series,DataFrame# n = np.nan# print(type(n)) #<class 'float'># print( 阅读全文
posted @ 2019-07-04 10:36 nikecode 阅读(2080) 评论(0) 推荐(0)
摘要:#Seriesimport numpy as npimport pandas as pd# s1 = pd.Series([1,2,3,4])# print(s1)# # 0 1# # 1 2# # 2 3# # 3 4# # dtype: int64# print(s1.values) #[1 2 阅读全文
posted @ 2019-07-04 10:35 nikecode 阅读(262) 评论(0) 推荐(0)
摘要:#数学基础回顾之矩阵运算#基本概念 #矩阵:矩形的数组,即二维数组。其中向量和标量都是矩阵的特例 #向量:是指1*n或者n*1的矩阵 #标量:1*1的矩阵 #数组:N维的数组,是矩阵的延伸#特殊矩阵: #全0全1矩阵 #单位矩阵#矩阵加减运算: #相加,减的两个矩阵必须要有相同的行和列 #行和列对应 阅读全文
posted @ 2019-07-04 10:33 nikecode 阅读(200) 评论(0) 推荐(0)
摘要:#数据科学领域五个最佳Python库#Numpy/Scipy/Pandas/Matplotlib/Scikit-learn#Numpy #N维数组(矩阵),快速高效,矢量数学运算 #高效的Index,不需要循环 #开源免费跨平台,运行效率足以和C/Matlab媲美#Scipy #依赖于numpy # 阅读全文
posted @ 2019-07-04 10:30 nikecode 阅读(439) 评论(0) 推荐(0)