python 数据读写 IO

1   TXT读写

# 写入txt_0=open('packages/txt_0.txt','w')  # w 只写 r 只读txt_0.write('写入数据到TXT')txt_0.close()# 读取txt_1=open('packages/txt_0.txt','r')print(txt_1.read())group =  pd.read_table('bayes.txt',header=None,usecols = (0,1,3))

2  Excel 读写

# 1 xlsxwriter 读取写入import xlsxwriter# 写入workbook = xlsxwriter.Workbook('packages/写入的XLSX.xlsx')worksheet = workbook.add_worksheet()N=0for i in range(101):    # print(i)    worksheet.write(N,0,i)    N=N+1workbook.close()print('写入成功')print('\n\n pandas读取写入 转为DataFrame用pd写入')# 读取import pandas as pdexcel_0=pd.read_excel('packages/写入的XLSX.xlsx')# print(excel_0)# 写入import numpy as npnp.random.seed(20)a=np.random.randn(10,10)# a=np.mat('2,3,4;2,3,4')print(a)# 转为pandas 的 DataFramedf=pd.DataFrame(a)df.to_excel('packages/写入的XLSX.xlsx')

3 pandas 读写 csv

# 写入a=np.mat('2,3,4;2,3,4')df=pd.DataFrame(a)df.to_csv('packages/csv_0.csv')# 读取df=pd.read_csv('packages/csv_0.csv')print(df)# 读取保存csv 添加列名group_0_1 =  pd.read_csv('DATA/Fly_0_1.csv',header=None)group_0_1.columns = ['Fly','Game','Table']print(group_0_1)group_0_1.to_csv('DATA/Fly_0_2.csv',index=None,usecols = (0,1,2))

4 HDF (注：没有运行成功！)

import tablesimport numpy as np from os.path import getsizefrom tempfile import NamedTemporaryFilenp.random.seed(42)a=np.random.randn(365,4)tmpf = NamedTemporaryFile()h5file = tables.openFile(tmpf.name,mode='w',title='NumpPy Array')root = h5file.rooth5file.createArray(root,'array',a)h5file.close()h5file = tables.openFile(tmpf.name,'r')print(getsize(tmpf.name))for node in h5file.iterNodes(h5file.root):b = node.read()print(type(b),b.shape)h5file.close()

5 HDF5仓库 HDFStore(注：没有运行成功！)

import numpy as npimport pandas as pdfrom tempfile import NamedTemporaryFilenp.random.seed(42)a = np.random.randn(365, 4)tmpf = NamedTemporaryFile()store = pd.io.pytables.HDFStore(tmpf.name)print( store)df = pd.DataFrame(a)store['df'] = dfprint( store)print( "Get", store.get('df').shape)print( "Lookup", store['df'].shape)print( "Dotted", store.df.shape)del store['df']print( "After del\n", store)print( "Before close", store.is_open)store.close()print( "After close", store.is_open)df.to_hdf(tmpf.name, 'data', format='table')print( pd.read_hdf(tmpf.name, 'data', where=['index>363']))

6 pandas Json 读写

import pandas as pdjson_str = '{"country":"Netherlands","dma_code":"0","timezone":"Europe\/Amsterdam","area_code":"0","ip":"46.19.37.108","asn":"AS196752","continent_code":"EU","isp":"Tilaa V.O.F.","longitude":5.75,"latitude":52.5,"country_code":"NL","country_code3":"NLD"}'# 读取Jsondata = pd.read_json(json_str, typ='series')print ("Series\n", data)# 写入data["country"] = "Brazil"print ("New Series\n", data.to_json())# 解析Jsonimport jsonimport requestsip = '50.78.253.58'html=requests.get('http://freegeoip.net/json/'+ip)respondjson=json.loads(html.text)print(respondjson.get('country_code'))

7 cv2 图片 读写

import cv2import numpy as np# 读取img = cv2.imread('packages/000.jpg')# 编辑img[50:150,50:150]=255img[:,:,2]=255img[300:600,300:600]=(200,200,0) #BGR# 显示图片cv2.imshow('2',img)cv2.waitKey()cv2.destroyAllWindows()# 写入图片cv2.imwrite('packages/Output.jpg',img)

8 全部代码：

print('----------1 TXT读写-----------\n')# 写入txt_0=open('packages/txt_0.txt','w')  # w 只写 r 只读txt_0.write('写入数据到TXT')txt_0.close()# 读取txt_1=open('packages/txt_0.txt','r')print(txt_1.read())group =  pd.read_table('bayes.txt',header=None,usecols = (0,1,3))print('\n\n----------------2 Excel 读写-----------------------')# 1 xlsxwriter 读取写入import xlsxwriter# 写入workbook = xlsxwriter.Workbook('packages/写入的XLSX.xlsx')worksheet = workbook.add_worksheet()N=0for i in range(101):    # print(i)    worksheet.write(N,0,i)    N=N+1workbook.close()print('写入成功')print('\n\n pandas读取写入 转为DataFrame用pd写入')# 读取import pandas as pdexcel_0=pd.read_excel('packages/写入的XLSX.xlsx')# print(excel_0)# 写入import numpy as npnp.random.seed(20)a=np.random.randn(10,10)# a=np.mat('2,3,4;2,3,4')print(a)# 转为pandas 的 DataFramedf=pd.DataFrame(a)df.to_excel('packages/写入的XLSX.xlsx')print('\n\n----------3 pandas 读写 csv----------------')# 写入a=np.mat('2,3,4;2,3,4')df=pd.DataFrame(a)df.to_csv('packages/csv_0.csv')# 读取df=pd.read_csv('packages/csv_0.csv')print(df)# 读取保存csv 添加列名group_0_1 =  pd.read_csv('DATA/Fly_0_1.csv',header=None)group_0_1.columns = ['Fly','Game','Table']print(group_0_1)group_0_1.to_csv('DATA/Fly_0_2.csv',index=None,usecols = (0,1,2))print('\n\n----------------4 HDF-运行失败----------------')import tablesimport numpy as np from os.path import getsizefrom tempfile import NamedTemporaryFilenp.random.seed(42)a=np.random.randn(365,4)tmpf = NamedTemporaryFile()h5file = tables.openFile(tmpf.name,mode='w',title='NumpPy Array')root = h5file.rooth5file.createArray(root,'array',a)h5file.close()h5file = tables.openFile(tmpf.name,'r')print(getsize(tmpf.name))for node in h5file.iterNodes(h5file.root):b = node.read()print(type(b),b.shape)h5file.close()print('\n\n------------------5 HDF5仓库 HDFStore-运行失败---------------------')import numpy as npimport pandas as pdfrom tempfile import NamedTemporaryFilenp.random.seed(42)a = np.random.randn(365, 4)tmpf = NamedTemporaryFile()store = pd.io.pytables.HDFStore(tmpf.name)print( store)df = pd.DataFrame(a)store['df'] = dfprint( store)print( "Get", store.get('df').shape)print( "Lookup", store['df'].shape)print( "Dotted", store.df.shape)del store['df']print( "After del\n", store)print( "Before close", store.is_open)store.close()print( "After close", store.is_open)df.to_hdf(tmpf.name, 'data', format='table')print( pd.read_hdf(tmpf.name, 'data', where=['index>363']))print('\n\n------------pandas Json---------------------')import pandas as pdjson_str = '{"country":"Netherlands","dma_code":"0","timezone":"Europe\/Amsterdam","area_code":"0","ip":"46.19.37.108","asn":"AS196752","continent_code":"EU","isp":"Tilaa V.O.F.","longitude":5.75,"latitude":52.5,"country_code":"NL","country_code3":"NLD"}'# 读取Jsondata = pd.read_json(json_str, typ='series')print ("Series\n", data)# 写入data["country"] = "Brazil"print ("New Series\n", data.to_json())# 解析Jsonimport jsonimport requestsip = '50.78.253.58'html=requests.get('http://freegeoip.net/json/'+ip)respondjson=json.loads(html.text)print(respondjson.get('country_code'))print('\n\n----------------------cv2 图片--------------------------')import cv2import numpy as np# 读取img = cv2.imread('packages/000.jpg')# 编辑img[50:150,50:150]=255img[:,:,2]=255img[300:600,300:600]=(200,200,0) #BGR# 显示图片cv2.imshow('2',img)cv2.waitKey()cv2.destroyAllWindows()# 写入图片cv2.imwrite('packages/Output.jpg',img)

9 参数：

参数Parameters:path_or_buf : string or file handle, default NoneFile path or object, if None is provided the result is returned as a string.sep : character, default ‘,’Field delimiter for the output file.na_rep : string, default ‘’Missing data representationfloat_format : string, default NoneFormat string for floating point numberscolumns : sequence, optionalColumns to writeheader : boolean or list of string, default TrueWrite out column names. If a list of string is given it is assumed to be aliases for the column namesindex : boolean, default TrueWrite row names (index)index_label : string or sequence, or False, default NoneColumn label for index column(s) if desired. If None is given, and header and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex. If False do not print fields for index names. Use index_label=False for easier importing in Rmode : strPython write mode, default ‘w’encoding : string, optionalA string representing the encoding to use in the output file, defaults to ‘ascii’ on Python 2 and ‘utf-8’ on Python 3.compression : string, optionala string representing the compression to use in the output file, allowed values are ‘gzip’, ‘bz2’, ‘xz’, only used when the first argument is a filenameline_terminator : string, default '\n'The newline character or character sequence to use in the output filequoting : optional constant from csv moduledefaults to csv.QUOTE_MINIMAL. If you have set a float_format then floats are comverted to strings and thus csv.QUOTE_NONNUMERIC will treat them as non-numericquotechar : string (length 1), default ‘”’character used to quote fieldsdoublequote : boolean, default TrueControl quoting of quotechar inside a fieldescapechar : string (length 1), default Nonecharacter used to escape sep and quotechar when appropriatechunksize : int or Nonerows to write at a timetupleize_cols : boolean, default Falsewrite multi_index columns as a list of tuples (if True) or new (expanded format) if Falsedate_format : string, default NoneFormat string for datetime objectsdecimal: string, default ‘.’Character recognized as decimal separator. E.g. use ‘,’ for European dataNew in version 0.16.0.