import pandas as pd
import numpy as np

objs
axis=0
keys
join='outer' / 'inner':表示的是级联的方式，outer会将所有的项进行级联（忽略匹配和不匹配），而inner只会将匹配的项级联到一起，不匹配的不级联
ignore_index=False

df1 = pd.DataFrame(data=np.rand...

import matplotlib.pyplot as plt
import numpy as np

#绘制单条线形图
x = np.array([1,2,3,4,5])
y = x + 3

plt.plot(x,y)

[<matplotlib.lines...

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv('city_temperature.csv',dtype={'State':object})


# In[2]:


data['AvgTemperature'] = (data['AvgTemperature']-32)/1.8


# In[3...

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv('city_temperature.csv',dtype={'State':object})

# 温度转换
data['AvgTemperature'] =(data['AvgT...

# -*- coding: utf-8 -*-

import pandas as pd
order = pd.read_table('../data/meal_order_info.csv',
      sep = ',',encoding = 'gbk')
print('进行转换前订单信息表lock_time的类型为：', 
      order['lock_time'].dtypes)
order['lock_time'] = pd.to_date...

 pip install pymysql sqlalchemy

import os
import pandas as pd
from sqlalchemy import create_engine

## 创建一个mysql连接器，用户名为root，密码为root123
## 地址为127.0.0.1，数据库名称为testdb，编码为utf-8
engine = create_engine(
    'mysql+pymysql://root:root123@127.0.0.1:3...

import numpy as np

# 1题 
arr1 = np.arange(9).reshape(3,3)

arr1.max(axis=1) # 对于二维数组来说，axis=0 对列操作，axis=1 对行操作

array([2, 5, 8])

# 2题
arr2 = np.arange(36).reshape(2,3,6)
arr2

array([[[ 0,  1,  2,  3,  4,  5],
        [ 6,  7,  8,  9, 10, 11],
        [12, 13, 14, 15, 16, 17]],

     ...

import tushare as ts
import pandas as pd
from pandas import DataFrame,Series
import numpy as np

import numpy as np

# 1.创建一个长度为10的ndarry对象，然后让第三个元素等于1

arr1 = np.zeros(10)
arr1[2] = 1
print(arr1)

# 2.创建10到49的ndarry对象

arr2 = np.arange(10, 50)
print(arr2)

# 3.反转arr2

arr3 = arr2[::-1]
print(arr3)

# 4.使用np.random.random

arr4 = np.random.random((10, 10))
print(arr4)
print(arr4.min())

# 5...