Python提取TXT数据转化为DataFrame

第一步：读取文本，open函数

第二步：处理文本，split函数

第三步：利用Numpy, pandas

import pandas as pd
import numpy as np
#打开txt文件
file_object=open("D:/test.txt")
try:
    file_content=file_object.read()
finally:
    file_object.close()
#利用逗号分隔
result=file_content.split(',')
#建立空的list存数据
a=[]
#依次读取
for i in result:
    a.append(i)
#将里面数字变成int
a=list(map(int,a))
#将其变成array
a=np.array(a)
#重组数据变成你想要的矩阵, 60*10
MAT=a.reshape((60,10))
#输出为excel
pd.Dataframe(MAT).to_excel("D:/处理过的txt.xlsx")

数据集（复制粘贴到txt文件练习即可）：

0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,145 ,169 ,255 ,255 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,255 ,0 ,0
 ,0 ,205 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,227 ,0 ,0 ,158 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,150 ,0 ,0 ,0 ,0 ,0 ,0 ,152 ,0 ,0 ,0 ,144
 ,0 ,139 ,0 ,148 ,0 ,0 ,0 ,0 ,0 ,153 ,0 ,0 ,148 ,0 ,0 ,0 ,0 ,0 ,154 ,0 ,0 ,0 ,0 ,58 ,156 ,0 ,0 ,0
 ,0 ,0 ,150 ,0 ,0 ,0 ,0 ,0 ,154 ,153 ,0 ,0 ,219 ,0 ,0 ,0 ,144 ,153 ,158 ,149 ,153 ,0 ,0 ,0
 ,150 ,148 ,0 ,0 ,0 ,154 ,143 ,0 ,145 ,0 ,152 ,0 ,154 ,148 ,153 ,162 ,148 ,155 ,146 ,0
 ,144 ,0 ,152 ,145 ,154 ,0 ,0 ,0 ,0 ,151 ,153 ,148 ,153 ,156 ,0 ,144 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0
 ,0 ,143 ,0 ,153 ,142 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,154 ,148 ,0 ,148 ,158 ,148 ,147 ,152 ,154
 ,158 ,155 ,150 ,150 ,0 ,151 ,0 ,148 ,151 ,157 ,152 ,149 ,148 ,150 ,145 ,153 ,151 ,153
 ,153 ,0 ,152 ,147 ,158 ,151 ,152 ,155 ,154 ,149 ,147 ,151 ,150 ,0 ,151 ,154 ,142 ,148
 ,149 ,0 ,152 ,151 ,0 ,146 ,147 ,147 ,151 ,148 ,146 ,154 ,153 ,149 ,0 ,151 ,153 ,149
 ,150 ,151 ,156 ,148 ,152 ,150 ,146 ,150 ,148 ,151 ,153 ,154 ,157 ,153 ,150 ,155 ,152
 ,150 ,149 ,152 ,150 ,147 ,149 ,0 ,150 ,152 ,149 ,151 ,0 ,152 ,149 ,154 ,152 ,158 ,154
 ,153 ,152 ,149 ,155 ,149 ,152 ,150 ,0 ,0 ,0 ,145 ,0 ,148 ,152 ,152 ,0 ,148 ,149 ,149 ,0
 ,151 ,159 ,152 ,151 ,0 ,157 ,153 ,0 ,151 ,149 ,152 ,151 ,0 ,146 ,0 ,0 ,152 ,150 ,0 ,148
 ,155 ,0 ,147 ,152 ,0 ,150 ,0 ,148 ,152 ,0 ,0 ,154 ,146 ,151 ,147 ,153 ,146 ,153 ,151 ,0
 ,0 ,0 ,152 ,0 ,149 ,157 ,0 ,146 ,149 ,151 ,154 ,0 ,0 ,0 ,0 ,153 ,0 ,0 ,0 ,148 ,0 ,0 ,0 ,0
 ,152 ,0 ,147 ,151 ,0 ,168 ,0 ,156 ,0 ,144 ,0 ,0 ,90 ,148 ,152 ,155 ,151 ,159 ,0 ,0 ,0 ,0 ,0
 ,159 ,0 ,0 ,0 ,158 ,0 ,0 ,152 ,0 ,0 ,0 ,0 ,157 ,0 ,0 ,0 ,0 ,156 ,0 ,0 ,0 ,0 ,255 ,0 ,0 ,0 ,0 ,0
 ,0 ,255 ,0 ,0 ,0 ,147 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,255 ,0 ,204 ,0 ,0 ,122 ,0 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,249 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,136 ,0 ,255 ,0 ,0 ,0 ,255 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,255 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,98 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,151 ,0 ,0 ,0 ,0
 ,0 ,0 ,0 ,0 ,0 ,0 ,0