python随机提取文件中的某一列的任意一个值？ python中如何提取一组数据中的第一列数据
python\u600e\u4e48\u63d0\u53d6\u51fa\u6587\u4ef6\u91cc\u7684\u6307\u5b9a\u5185\u5bb9python\u8bfb\u53d6\u6587\u4ef6\u5185\u5bb9\u7684\u65b9\u6cd5\uff1a
\u4e00.\u6700\u65b9\u4fbf\u7684\u65b9\u6cd5\u662f\u4e00\u6b21\u6027\u8bfb\u53d6\u6587\u4ef6\u4e2d\u7684\u6240\u6709\u5185\u5bb9\u5e76\u653e\u7f6e\u5230\u4e00\u4e2a\u5927\u5b57\u7b26\u4e32\u4e2d\uff1a
all_the_text = open('thefile.txt').read( )# \u6587\u672c\u6587\u4ef6\u4e2d\u7684\u6240\u6709\u6587\u672call_the_data = open('abinfile','rb').read( )# \u4e8c\u8fdb\u5236\u6587\u4ef6\u4e2d\u7684\u6240\u6709\u6570\u636e
\u4e3a\u4e86\u5b89\u5168\u8d77\u89c1\uff0c\u6700\u597d\u8fd8\u662f\u7ed9\u6253\u5f00\u7684\u6587\u4ef6\u5bf9\u8c61\u6307\u5b9a\u4e00\u4e2a\u540d\u5b57\uff0c\u8fd9\u6837\u5728\u5b8c\u6210\u64cd\u4f5c\u4e4b\u540e\u53ef\u4ee5\u8fc5\u901f\u5173\u95ed\u6587\u4ef6\uff0c\u9632\u6b62\u4e00\u4e9b\u65e0\u7528\u7684\u6587\u4ef6\u5bf9\u8c61\u5360\u7528\u5185\u5b58\u3002\u4e3e\u4e2a\u4f8b\u5b50\uff0c\u5bf9\u6587\u672c\u6587\u4ef6\u8bfb\u53d6\uff1a
file_object = open('thefile.txt')try:all_the_text = file_object.read( )finally:file_object.close( )
\u4e0d\u4e00\u5b9a\u8981\u5728\u8fd9\u91cc\u7528Try/finally\u8bed\u53e5\uff0c\u4f46\u662f\u7528\u4e86\u6548\u679c\u66f4\u597d\uff0c\u56e0\u4e3a\u5b83\u53ef\u4ee5\u4fdd\u8bc1\u6587\u4ef6\u5bf9\u8c61\u88ab\u5173\u95ed\uff0c\u5373\u4f7f\u5728\u8bfb\u53d6\u4e2d\u53d1\u751f\u4e86\u4e25\u91cd\u9519\u8bef\u3002
\u4e8c.\u6700\u7b80\u5355\u3001\u6700\u5feb\uff0c\u4e5f\u6700\u5177Python\u98ce\u683c\u7684\u65b9\u6cd5\u662f\u9010\u884c\u8bfb\u53d6\u6587\u672c\u6587\u4ef6\u5185\u5bb9\uff0c\u5e76\u5c06\u8bfb\u53d6\u7684\u6570\u636e\u653e\u7f6e\u5230\u4e00\u4e2a\u5b57\u7b26\u4e32\u5217\u8868\u4e2d\uff1alist_of_all_the_lines = file_object.readlines( )
\u8fd9\u6837\u8bfb\u51fa\u7684\u6bcf\u884c\u6587\u672c\u672b\u5c3e\u90fd\u5e26\u6709"\n"\u7b26\u53f7\uff1b\u5982\u679c\u4f60\u4e0d\u60f3\u8fd9\u6837\uff0c\u8fd8\u6709\u53e6\u4e00\u4e2a\u66ff\u4ee3\u7684\u529e\u6cd5\uff0c\u6bd4\u5982\uff1alist_of_all_the_lines = file_object.read( ).splitlines( )list_of_all_the_lines = file_object.read( ).split('\n')list_of_all_the_lines = [L.rstrip('\n') for L in file_object]
1\u3001Python
Python(\u82f1\u8bed\u53d1\u97f3:/ˈpaɪ\u03b8ən/), \u662f\u4e00\u79cd\u9762\u5411\u5bf9\u8c61\u3001\u89e3\u91ca\u578b\u8ba1\u7b97\u673a\u7a0b\u5e8f\u8bbe\u8ba1\u8bed\u8a00\uff0c\u7531Guido van Rossum\u4e8e1989\u5e74\u5e95\u53d1\u660e\uff0c\u7b2c\u4e00\u4e2a\u516c\u5f00\u53d1\u884c\u7248\u53d1\u884c\u4e8e1991\u5e74\uff0cPython \u6e90\u4ee3\u7801\u540c\u6837\u9075\u5faa GPL(GNU General Public License)\u534f\u8bae\u3002
2\u3001\u57fa\u672c\u6982\u5ff5
Python\uff08KK \u82f1\u8bed\u53d1\u97f3\uff1a/'paɪ\u03b8\u0251n/, DJ \u82f1\u8bed\u53d1\u97f3\uff1a/ˈpai\u03b8ən/\uff09\u662f\u4e00\u79cd\u9762\u5411\u5bf9\u8c61\u3001\u76f4\u8bd1\u5f0f\u8ba1\u7b97\u673a\u7a0b\u5e8f\u8bbe\u8ba1\u8bed\u8a00\uff0c\u7531Guido van Rossum\u4e8e1989\u5e74\u5e95\u53d1\u660e\u3002
\u6982\u8ff0\u76f4\u63a5\u63d0\u53d6\u4f1a\u62a5\u9519\uff0c\u628aarray\u6570\u7ec4\u8f6c\u6362\u6210list\uff0c\u5373\u53ef\u63d0\u53d6\uff0c\u4f7f\u7528numpy\u8f6c\u6362
\u6b65\u9aa4\u8be6\u89e31\u3001\u76f4\u63a5\u63d0\u53d6\u5c1d\u8bd5\uff1a
group=[[1,2],[2,3],[3,4]]
#\u63d0\u53d6\u7b2c\u4e00\u5217\u5143\u7d20
print(group[:,1])
#Out:TypeError: list indices must be integers or slices, not tuple
2\u3001\u4f7f\u7528numpy\u8f6c\u6362\uff1a
import numpy as np
group=[[1,2],[2,3],[3,4]]
#numpy\u8f6c\u5316
ar=np.array(group)
print(ar[:,1])
#Out:[2 3 4]
\u62d3\u5c55\u5185\u5bb9numpy\u8be6\u89e3
Numpy\u5bf9\u8c61\u662f\u6570\u7ec4\uff0c\u79f0\u4e3andarray \u7ef4\u5ea6(dimensions)\u79f0\u4f5c\u8f74(axes),\u8f74\u7684\u4e2a\u6570\u53eb\u505a\u79e9(rank)\u3002\u6ce8\uff1a\u6709\u51e0\u7ea7\u4e2d\u62ec\u53f7\u5c31\u6709\u51e0\u4e2a\u7ef4\u5ea6
\u4e00\u3001ndarray.attrs:
ndarray.ndim \u79e9
ndarray.shape \u4f8b\u5982\u4e00\u4e2a2\u63923\u5217\u7684\u77e9\u9635\uff0c\u5b83\u7684shape\u5c5e\u6027\u662f(2,3)
ndarray.size \u6570\u7ec4\u5143\u7d20\u7684\u603b\u4e2a\u6570
ndarray.dtype \u5143\u7d20\u7c7b\u578b\uff0cNumPy\u63d0\u4f9b\u81ea\u5df1\u7684\u6570\u636e\u7c7b\u578b
ndarray.itemsize \u6570\u7ec4\u4e2d\u6bcf\u4e2a\u5143\u7d20\u7684\u5b57\u8282\u5927\u5c0f
\u4e8c\u3001\u6570\u7ec4\u521b\u5efa\u51fd\u6570\uff1a
array
asarray\u5c06\u8f93\u5165\u8f6c\u6362\u6210ndarray
arange
ones
zeros
empty \u53ea\u5206\u914d\u5185\u5b58\u7a7a\u95f4\u4e0d\u586b\u5145\u4efb\u4f55\u503c
eye \u521b\u5efaN*N\u5355\u4f4d\u77e9\u9635(\u5bf9\u89d2\u7ebf\u4e3a1)
\u4e09\u3001\u6570\u7ec4\u548c\u6807\u91cf\u4e4b\u95f4\u7684\u8fd0\u7b97
numpy\u6570\u7ec4\u7684\u4e00\u4e2a\u7279\u70b9\uff0c\u4e0d\u7528\u7f16\u5199\u5faa\u73af\u5c31\u53ef\u5bf9\u6570\u636e\u6267\u884c\u6279\u91cf\u8fd0\u7b97\uff0c\u8fd9\u901a\u5e38\u79f0\u4f5c\u77e2\u91cf\u5316(vectorization)\u3002
\u56db\u3001\u57fa\u672c\u7684\u7d22\u5f15\u548c\u5207\u7247
numpy\u6570\u7ec4\u7684\u7d22\u5f15\u662f\u4e00\u4e2a\u5185\u5bb9\u4e30\u5bcc\u7684\u4e3b\u9898\uff0c\u56e0\u4e3a\u9009\u53d6\u6570\u636e\u5b50\u96c6\u6216\u5355\u4e2a\u5143\u7d20\u7684\u65b9\u5f0f\u6709\u5f88\u591a\u3002\u8fd9\u91cc\u6211\u4ec5\u8be6\u7ec6\u4ecb\u7ecd\u5e38\u7528\u7684\u65b9\u6cd5\uff0c\u5bf9\u4e8e\u9ad8\u7ea7\u529f\u80fd\u7684\u65b9\u5f0f\u6211\u5217\u4e3e\u540d\u79f0\uff0c\u8bfb\u8005\u53ef\u4ee5\u7b49\u5230\u8981\u7528\u7684\u65f6\u5019\u81ea\u884c\u67e5\u9605\u8d44\u6599\u3002
需要某列的某个值?
文本格式
1 2 3
4 5 6
如果是文本的话首先f.readlines()获得所有行，
然后用随机函数， random.choice(array)随机获得列
strs.split()值转换成列表
再用随机函数random.choice(strs)
随机获得一个元素
如果是单元格的话
就是先获取单元格的行和列
然后用随机函数
random.randint(0, 有效行)
random.randint(0, 有效列)
table.cell_value(列,行)
就能获取任意值了
绛旓細import re 鏂囨湰涓殑鎵鏈夊瓧娈靛悕绉 split_words = ("鍏徃鍏ㄧО", "瀹㈡埛濮撳悕", "鑱旂郴鏂瑰紡" , ...)浣犻渶瑕佺殑瀛楁鍚嶇О,鐢▅鍒嗗壊 need_words = "鍏徃鍏ㄧО|瀹㈡埛濮撳悕|鑱旂郴鏂瑰紡 ..."with open("a.txt", "r") as f:txt = f.read()鎶婂悇瀛楁鍒嗙鍑烘潵鏂逛究鎻愬彇 for i in split_words:txt = txt....
绛旓細-*- coding: utf-8 -*-import randomwith open('a.txt','r') as f: with open('b.txt','w') as f2: lines=f.readlines() flen=len(lines)-1 for i in range(1,random.randint(0,flen)): f2.write(lines[random.randint(0,flen)])...
绛旓細import os,shutilfor filename in open(result.out): shutil.copy(os.path.join(r'鏂囦欢澶A'锛宖ilename+'.mol'),r'鏂囦欢澶笲')
绛旓細姣斿锛歭ine = 鈥123456789abcdefghijklmnopqrstuvwxyz鈥濊鑾峰彇鈥渕n鈥濆墠鐨勬墍鏈夊瓧绗︿覆鍐呭锛歱rint(line[0:line.rfind('mn')]) #涓嶅寘鎷瓧绗︹渕n鈥濊緭鍑虹粨鏋滐細123456789abcdefghijkl 瑕佽幏鍙栤渕n鈥濆紑濮嬬殑鎵鏈夊瓧绗︿覆鍐呭锛歱rint(line[line.rfind('mn'):]) #鍖呮嫭瀛楃鈥渕n鈥濊緭鍑虹粨鏋滐細mnopqrstuvwxyz ...
绛旓細): linea=linea.replace("\n","").split("\t") fp-1.writeline(linea[0]) fp-2.writeline(linea[1])fpa.close()fp-1.close()fp-2.close()棣栧厛鎵撳紑鏁版嵁瀛樻斁鐨鏂囦欢杩涜锛岃鎿嶄綔锛涚劧鍚庢墦寮涓や釜鍐欐枃浠讹紝濡傛灉涓嶅瓨鍦紝鍙互鐩存帴鍒涘缓锛涙寜琛岃鍙栵紝鐒跺悗鍒嗗壊锛屽垎鍒啓鍏ヤ笉鍚岀殑鏂囦欢銆
绛旓細class stdata(Structure):_fields_ = [('pBuf', c_char_p), ('buflen', c_int)]N=100 buf = create_string_buffer(N)d = stdata()d.buflen = N d.pBuf = cast(buf, c_char_p)n = CallMyCFunc_GetData(byref(d))鍏抽敭鍦ㄤ簬create_string_buffer鍒涘缓鍙啓buffer锛沜ast杞崲涓篶har*...
绛旓細鍒嗕袱姝ワ細step1锛 鑾峰彇瀛鏂囦欢 --> os.walk step2锛歳ead 鏂囦欢 --> 鑷繁鍐欏暒 鎴戝啓浜嗕釜绠鍗曠殑锛屼綘鑷繁鏀规敼 import osdef getfiles(path = None): path = os.path.abspath(path) if path else os.getcwd() for parent,folders,files in os.walk(path): if not files: continue ...
绛旓細1銆佺15琛岀殑7锛岃繖鏄滃疄闄呭叆搴撴暟閲忊濈殑鍒楁暟 2銆佺17琛岀殑鈥滃疄闄呭叆搴撴暟閲忊濓紝杩欐槸鍒楀悕 杩欐槸csv鏁版嵁鐨勬牱寮忥紝鍒楁暟鏄熀浜0寮濮嬬殑 coding=gbkimport globimport pandas as pd# 鍒濆鍖栵紝姝ゅ彉閲忕敤鏉ヨ鎵鏈塩sv鏁版嵁all_data_frames = []# 浣跨敤glog.glob鎵惧埌鎵鏈塩sv鏂囦欢骞跺皢鎵鏈夋暟鎹斁鍒癮ll_data_frames涓...
绛旓細渚媕son鏂囦欢锛屽悕瀛梩est.json锛寋 "verson":"1.4.2" , "author":"johanna", "type":"1"} python缂栫爜:棣栧厛璇诲彇json鏂囦欢鍐呭锛屽埄鐢╦son.loads()杞寲涓篸ict绫诲瀷锛岄亶鍘嗘瘡涓瀵筴ey,val import jsonimport ostry:t_str = open('./test.json','r').read()t_json = json.loads(t_str)for k,v ...
绛旓細s1='''14441439 723 40 14451440 740 43 144614411710 48 14471442 706 43 144814432731 49'''s2='''14151410 800 43 14171412 824 44 141914142837 46 14201415 816 43 14221417 783 43'''data=[]for s in (s1,s2):line=s.splitlines()data.append(line[3][9:12])data....
