Python数据分析numpy文本数据读取索引切片实例详解

import numpy as np
filepath = './doubantop250.csv'
t1 = np.loadtxt(filepath,usecols=(1,2,3),delimiter=',',dtype='float')
print(t1)
# 转置的四种方式
# first method:Set the value of parameter "unpack" —— True
t2 = np.loadtxt(filepath,usecols=(1,2,3),delimiter=',',dtype='float',unpack=True)
# second method: use the '.T' attributions of array's
t3 = t1.T
print(t3)
# third method: use the method of 'transpose'
t4 = t1.transpose()
print(t4)
# forth method: swapaxes(arguments：axes needed swapped)
t5 = t1.swapaxes(0,1)
print(t5)

import numpy as np
filename = './doubantop250.csv'
t1 = np.loadtxt(filename,delimiter=',',dtype='float',usecols=(1,2,3))
# print(t1)
# 取行操作
print(t1[0])
print(t1[0,:])
# 取连续的多行
print(t1[3:])
print(t1[3:,:])
# 取不连续的多行
print(t1[[1,3,13,19]])
print(t1[[1,2,4,6],:])
# 取列
print(t1[:,0])
# 取连续的列
print(t1[:,2:])
# 取不连续的列
print(t1[:,[1,2]])
# 取第2-5行，2-3列
# 取多个位置的交叉数据
print(t1[1:5,1:3])
# 取不相邻的位置的数据信息
print(t1[[1,4,6],[0,1,2]])

import numpy as np
filepath = './doubantop250.csv'
t1 = np.loadtxt(filepath,delimiter=',',usecols=(1,2,3))
print(t1<9.5)
t1[t1 < 9.5] = 0
print(t1[:,1])
# if-else操作
np.where(t1>=9.6,10,0)
print(t1)
# clip(m,n)把数组中小于m的替换成m,大于n的替换成n