python对CSV、Excel、txt

#3.读取csv至字典x,y
import csv

# 读取csv至字典
csvFile = open(r'G:\训练小样本.csv', "r")
reader = csv.reader(csvFile)
#print(reader)

# 建立空字典
result = {}

i=0
for item in reader:
    if reader.line_num==1:
        continue
    result[i]=item
    i=i+1

 # 建立空字典   
j=0
xx={}
yy={}
for i in list(range(29)):
    xx[j]=result[i][1:-1]
    yy[j]=result[i][-1]
    # print(x[j])
    # print(y[j])
    j=j+1

csvFile.close()

##3.1字典转换成list
X=[]
Y=[]
for i in xx.values():
    X.append(i)

for j in xx.values():
    X.append(j)    

#加载数据  
def loadCSV(filename):  
    dataSet=[]  
    with open(filename,'r') as file:  
        csvReader=csv.reader(file)  
        for line in csvReader:  
            dataSet.append(line)  
    return dataSet  

读取的方式，是一行一行读取。

import pandas as pd
test_df = pd.read_csv(r'G:\test_linearRegression.csv',  sep = '\t', header = None)

import csv

#程序三
with open(r'G:\0pythonstudy\chengxu\test.csv','w',newline='') as myFile:      
    myWriter=csv.writer(myFile)  
    myWriter.writerow([7,'g'])  
    myWriter.writerow([8,'h'])  
    myList=[[1,2,3],[4,5,6]]  
    myWriter.writerows(myList)  
    
# myFile.close()

with open(r'G:\0pythonstudy\chengxu\test.csv',"r") as data:
    result=csv.reader(data)
    for item in result:
        print(item)

#1、导入模块

import xlrd

#2、打开Excel文件读取数据

data = xlrd.open_workbook('test_data.xlsx')
# print('data',data)

#3、使用技巧

#获取一个工作表
table = data.sheets()[0]          #通过索引顺序获取
# print('table',table)
print(table.nrows)#table 行数
print(table.ncols)
table = data.sheet_by_index(0) #通过索引顺序获取
# print('table',table)
table = data.sheet_by_name(u'Sheet1')#通过名称获取
 
# 获取整行和整列的值（数组）

i=1
print(table.row_values(i))#获得第i行数据

print(table.col_values(i))#获得第i列数据

9
2
[2.0, 6.0]
[5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0]

import pandas as pd
test_df = pd.read_excel(r'G:\test.xlsx')

c = np.fromfile('test2.dat', dtype=int)

a = numpy.loadtxt('odom.txt') 

a [[  2.49870000e-01
    2.50250000e-01
 [  3.64260000e+03
    3.72430000e+03
 [  4.53960000e+03
    4.50590000e+03
 ...,
 [  4.74110000e+01
    4.89660000e+01
 [  4.10930000e+01
    4.20480000e+01
 [  1.83510000e+01
    1.68250000e+01
a.shape (52, 500)