我们想把NaN缺失值给处理掉 1. 如何处理NAN判断数据是否是NAN:pd.isnull(df)pd.notnull(df)处理方式:存在缺失值nan，并且是np.nan 删除存在缺失值的:dropna(axis='rows') 替换缺失值:filena(...

能读取和保存的格式如下 1. CSV读取csvpandas.read_csv(filepath,sep=',')filepath:文件路径usecols:制定读取的列名，列表形式 读取open和close列import pandas as pd stock_data = pd.read_c...

1. 算数运算准备数据import pandas as pdstock_data = pd.read_csv('/root/Documents/stock_data.csv')print(stock_data) 2. 算数运算加法close列全体加10print(stock_data['close'].add(10))...

准备数据import pandas as pd stock_data = pd.read_csv('/root/Documents/stock_data.csv') print(stock_data) 1. 赋值操作stock_data['volume'] = 100 print(stock_data)都变成了100或者使用...

准备数据import pandas as pd stock_data = pd.read_csv('/root/Documents/stock_data.csv') print(stock_data) 1. 直接索引索引的时候必须列在前 行在后我现在想索引open列 第0行的数据print(...

1. Pandas以Numpy为基础，借力Numpy模块在计算方面性能高的优势基于mataplotlib，能够简便的画图独特的数据结构读取文件方便封装了mataplotlib，Numpy的画图和计算 用下例来观察pandas输出和直...

1. 单个数组运算import numpy as np arr = np.array([1, 2, 3, 4]) print(arr) arr = arr + 1 print(arr) arr = arr / 2 print(arr) arr = arr * 2 print(arr) 2. 两个数组运算import numpy as...

1. 数组形状修改import numpy as np score = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15], [16, 17, 18, 19, 20], [21, 22, 23, 24, 25], [26, 27, 28, 29, 30], [31, ...

1. ndarray与python原生list运算效率对比import random import time import numpy as np a = [] for i in range(100000000): a.append(random.random()) %time sum1 = sum(a) b = np.array(a) %...

1. 散点图import matplotlib.pyplot as plt import random x = [216.44167969458076, 240.4966574756141, 249.8230754557984, 245.2321537140637, 226.77839704071914, 294.69374551492643, 253...