摘要:
import pandas as pd pd.options.display.max_rows = 10 # 设置显示行数 #读入是直接指定索引 df1 = pd.read_csv(r'E:\anacondatest\PythonData\高校信息.csv', encoding='gbk', ind 阅读全文
摘要:
import pandas as pd pd.options.display.max_rows = 10#设置显示行数 df1 = pd.read_csv(r'E:\anacondatest\PythonData\高校信息.csv',encoding='gbk') #数据框基本信息 df1.info 阅读全文
摘要:
import pandas as pd import sqlalchemy import create_engine # 读取 pd.options.display.max_rows = 10#设置显示行数 df1 = pd.read_csv(r'E:\anacondatest\PythonData 阅读全文
摘要:
import pandas as pd print(pd.__version__) pd.options.display.max_rows = 10#设置显示行数 df1 = pd.DataFrame( { 'var1':[1,2,3], 'var2':[1,2,3], 'var3':'a' } ) 阅读全文
摘要:
import numpy as np # 二维数组 t1 = np.array([range(10),range(10,20)]) print(t1) # 三维数组 t2 = np.array([[range(10),range(10,20)],[range(10),range(10,20)]]) 阅读全文
摘要:
import numpy as np import random # 使用numpy生成数组的三种方式 t1 = np.array([1,2,3]) print(t1) t2 = np.array(range(10)) print(t2) t3 = np.arange(0,10,2) print(t 阅读全文
摘要:
from matplotlib import pyplot as plt import matplotlib import random a = [] for i in range(250): a.append(random.randint(80, 150)) # normed将频数分布变成频率分布 阅读全文
摘要:
from matplotlib import pyplot as plt import matplotlib # 设置字体大小 font = {'family':'MicroSoft YaHei', 'weight':'bold', 'size':8} matplotlib.rc("font",** 阅读全文
摘要:
from matplotlib import pyplot as plt import matplotlib # 设置字体大小 font = {'family':'MicroSoft YaHei', 'weight':'bold', 'size':8} matplotlib.rc("font",** 阅读全文
摘要:
from matplotlib import pyplot as plt import matplotlib # 设置字体大小 font = {'family':'MicroSoft YaHei', 'weight':'bold', 'size':8} matplotlib.rc("font",** 阅读全文