1銆佹?庢牱鍙栭噸澶嶅悕

鍦ㄦ棩甯哥敓娲讳腑锛屾垜浠父甯镐細閬囧埌閲嶅悕鐨勭儲鎭笺?備负浜嗛伩鍏嶆贩娣嗭紝鍙栦竴涓噸澶嶇殑鍚嶅瓧鍙兘鏄竴涓畝鍗曠殑瑙ｅ喅鏂规銆備互涓嬫槸涓?浜涘浣曞彇閲嶅鍚嶇殑鎶?宸э細

1. 娣诲姞鍦板悕锛?/p>

鍦ㄥ悕瀛楀墠闈㈡垨鍚庨潰鍔犱笂鍦板悕锛屽彲浠ュ尯鍒嗗悓鍚嶄笉鍚屼汉銆備緥濡傦紝鍚屽悕鐨勫皬鏄庡彲浠ュ彇鍚嶄负鈥滄睙鑻忓皬鏄庘?濇垨鈥滄渤鍗楀皬鏄庘?濄??/p>

2. 娣诲姞鑱屼笟淇℃伅锛?/p>

鍦ㄥ悕瀛楀悗娣诲姞鑱屼笟淇℃伅锛屽彲浠ヤ綋鐜颁釜浜虹殑宸ヤ綔鎬ц川銆備緥濡傦紝鍚屽悕鐨勫伐绋嬪笀鍙互璁╄嚜宸辩殑鍚嶅瓧涓衡?滃紶宸モ?濄??/p>

3. 娣诲姞杈堝垎锛?/p>

鍦ㄥ鏃忎腑锛屽悓鍚嶇殑浜叉垰鍙互浣跨敤杈堝垎鏉ュ尯鍒嗐?備緥濡傦紝鍚屽悕鐨勫瓩瀛愬彲浠ュ彇鍚嶄负鈥滃ぇ瀛欌?濇垨鈥滃皬瀛欌?濄??/p>

4. 娣诲姞鏄电О锛?/p>

鏄电О閫氬父鏄翰瀵嗙殑浜哄鑷繁鐨勭О鍛硷紝鍏锋湁鐙壒鐨勪釜浜鸿壊褰┿?傚悓鍚嶇殑鏈嬪弸鍙互缁欒嚜宸卞彇涓?涓樀绉帮紝濡傗?滃皬鏄庘?濆拰鈥滃皬鏄庡瓙鈥濄??/p>

5. 娣诲姞璋愰煶瀛楋細

灏嗗悓鍚嶇殑瀛楁媶鍒嗘垨鏇挎崲涓鸿皭闊冲瓧锛屽彲浠ュ垱閫犲嚭涓嶅悓鐨勫悕瀛椼?備緥濡傦紝鍚屽悕鐨勨?滄潕鍗庘?濆彲浠ュ彇鍚嶄负鈥滈噷鍖栤?濇垨鈥滀附鍗庘?濄??/p>

娉ㄦ剰浜嬮」锛?/p>

鍙栭噸澶嶅悕鏃堕渶瑕佹敞鎰忎互涓嬪嚑鐐癸細

閬垮厤浣跨敤杩囦簬甯歌鐨勯噸澶嶅悕锛屼互鍏嶆洿鍔犳贩娣嗐??/p>

閫夋嫨鏈夋剰涔夋垨璁板繂鐐圭殑閲嶅鍚嶏紝鏂逛究浠栦汉杈ㄨ銆?/p>

鑰冭檻涓庤嚜宸辩殑瀹為檯鎯呭喌鍜屽枩濂界浉绗︾殑閲嶅鍚嶃??/p>

鍦ㄦ寮忓満鍚堬紝鍙兘闇?瑕佷娇鐢ㄥ師鍚嶆潵閬垮厤璇細銆?/p>

閫氳繃宸у鍦板彇閲嶅鍚嶏紝鎴戜滑鍙互鏈夋晥瑙ｅ喅鍚屽悕甯︽潵鐨勪笉渚匡紝璁╄嚜宸辩殑鍚嶅瓧鏇?鍔犵嫭涓?鏃犱簩銆?/p>

2銆佹?庝箞鎶婇噸澶嶇殑鍚嶅瓧鍗曚釜鎻愬彇鍑烘潵

濡備綍灏嗛噸澶嶇殑鍚嶅瓧浠庡垪琛ㄤ腑鎻愬彇鍑烘潵

鎻愬彇閲嶅濮撳悕鏄暟鎹竻娲楀拰鍒嗘瀽涓殑甯歌浠诲姟銆備互涓嬫槸灏嗛噸澶嶅鍚嶄粠鍒楄〃涓彁鍙栧嚭鏉ョ殑姝ラ锛?/p>

1. 灏嗗垪琛ㄨ浆鎹负鏁版嵁妗嗘灦

灏嗗寘鍚鍚嶅垪琛ㄧ殑鏂囨湰鏂囦欢杞崲涓烘暟鎹鏋躲?傝繖灏嗗厑璁告偍瀵规暟鎹繘琛屾搷浣溿??/p>

2. 鍒犻櫎閲嶅琛?/p>

浣跨敤 `drop_duplicates()` 鍑芥暟鍒犻櫎鍖呭惈閲嶅濮撳悕鐨勮銆傛鍑芥暟灏嗘牴鎹寚瀹氬垪锛堝湪杩欑鎯呭喌涓嬩负濮撳悕鍒楋級鍒犻櫎閲嶅琛屻??/p>

df = df.drop_duplicates(subset=['濮撳悕'])

3. 閫夋嫨閲嶅鐨勮

瑕侀?夋嫨鍖呭惈閲嶅濮撳悕鐨勮锛屽彲浠ヤ娇鐢?`duplicated()` 鍑芥暟銆傛鍑芥暟灏嗚繑鍥炰竴涓竷灏斿?兼暟缁勶紝鍏朵腑 True 琛ㄧず閲嶅琛岋紝False 琛ㄧず鍞竴琛屻??/p>

```

duplicated_rows = df[df['濮撳悕'].duplicated()]

```

4. 鎻愬彇閲嶅鐨勫鍚?/p>

浣跨敤 `duplicated_rows` 閫夋嫨閲嶅琛屽悗锛屾偍鍙互鎻愬彇閲嶅鐨勫鍚嶃??/p>

```

duplicate_names = duplicated_rows['濮撳悕'].unique()

```

5. 杈撳嚭缁撴灉

灏嗛噸澶嶇殑濮撳悕杈撳嚭鍒版枃鏈枃浠舵垨鏄剧ず鍦ㄥ睆骞曚笂銆?/p>

```

print(duplicate_names)

```

绀轰緥

鍋囪鎮ㄦ湁涓?涓寘鍚互涓嬪鍚嶇殑鏂囨湰鏂囦欢锛?/p>

```

寮犱笁

鏉庡洓

鐜嬩簲

寮犱笁

璧靛叚

```

鎸夌収涓婅堪姝ラ锛屾偍鍙互鎻愬彇閲嶅鐨勫鍚嶏細

```

import pandas as pd

df = pd.read_csv('names.txt', names=['濮撳悕'])

df = df.drop_duplicates(subset=['濮撳悕'])

duplicated_rows = df[df['濮撳悕'].duplicated()]

duplicate_names = duplicated_rows['濮撳悕'].unique()

print(duplicate_names)

```

杈撳嚭锛?/p>

```

['寮犱笁']

```

3銆侀噸澶嶅悕瀛楁?庝箞绛涢?夊嚭鏉?/h3>

閲嶅鍚嶅瓧鐨勭瓫閫?/p>

鍦ㄥ鐞嗗ぇ鎵归噺鏁版嵁鏃讹紝闅惧厤浼氶亣鍒伴噸澶嶇殑濮撳悕锛岃繖缁欏悗缁垎鏋愬拰澶勭悊甯︽潵浜嗕笉渚裤?備负浜嗛珮鏁堢瓫閫夊嚭閲嶅鍚嶅瓧锛屽彲浠ラ噰鍙栦互涓嬫楠わ細

1. 鏁版嵁棰勫鐞?/p>

鏍囧噯鍖栧鍚嶆牸寮忥細灏嗗鍚嶇粺涓?涓虹浉鍚岀殑鏍煎紡锛屽鍏ㄦ嫾鎴栨嫾闊崇缉鍐欍??/p>

鍘婚櫎绌烘牸鍜岀壒娈婂瓧绗︼細鍘婚櫎濮撳悕涓殑绌烘牸鍜岀壒娈婂瓧绗︼紝濡傞?楀彿鍜屽彞鍙枫??/p>

2. 姣旇緝绠楁硶閫夋嫨

甯哥敤鐨勬瘮杈冪畻娉曟湁锛?/p>

绮剧‘鍖归厤锛氫弗鏍兼瘮杈冨鍚嶆槸鍚﹀畬鍏ㄧ浉鍚屻??/p>

鐩镐技搴︽瘮杈冿細瀵瑰鍚嶈繘琛屾ā绯婃瘮杈冿紝鍏佽涓?瀹氱▼搴︾殑宸紓銆?/p>

3. 绛涢?夋柟娉?/p>

鍝堝笇琛細灏嗘爣鍑嗗寲鍚庣殑濮撳悕杞崲?负鍝堝笇鍊硷紝鍒╃敤鍝堝笇琛ㄥ揩閫熸煡鎵鹃噸澶嶅?笺??/p>

鎺掑簭姣旇緝锛氬濮撳悕杩涜鎺掑簭鍚庯紝閫愪釜姣旇緝鐩搁偦濮撳悕鏄惁鐩稿悓銆?/p>

4. 鍏蜂綋瀹炵幇

浠?Python 涓轰緥锛屽彲浠ヤ娇鐢ㄥ涓嬩唬鐮佸疄鐜伴噸澶嶅悕瀛楃殑绛涢?夛細

```python

import hashlib

def compare_names(name1, name2):

return hashlib.md5(name1.encode('utf-8')).hexdigest() == hashlib.md5(name2.encode('utf-8')).hexdigest()

names = ['寮犱笁', '鏉庡洓', '鐜嬩簲', '寮犱笁']

unique_names = []

for name in names:

if compare_names(name, unique_names):

continue

else:

unique_names.append(name)

print(unique_names) 杈撳嚭锛歔'寮犱笁', '鏉庡洓', '鐜嬩簲']

```

娉ㄦ剰浜嬮」

姣旇緝绠楁硶鐨勯?夋嫨闇?瑕佹牴鎹暟鎹殑鍏蜂綋鎯呭喌杩涜璋冩暣銆?/p>

瀵逛簬闀垮害杈冮暱鐨勫鍚嶏紝妯＄硦姣旇緝鍙兘浼氫骇鐢熶笉鍑嗙‘鐨勭粨鏋溿??/p>

绛涢?夊悗鐨勭粨鏋滈渶瑕佷汉宸ュ鏍革紝浠ョ‘淇濆噯纭?с??/p>

4銆佹?庢牱鍙栭噸澶嶅悕瀛楃殑缃戝悕

濡備綍鍙栭噸澶嶇綉鍚?/p>

鍙栭噸澶嶇綉鍚嶇殑鎶?宸у緢绠?鍗曘?傞?夋嫨涓?涓父鐢ㄧ殑鍚嶅瓧锛屼緥濡傗?滃皬鏄庘?濇垨鈥滃皬绾⑩?濄?傜劧鍚庯紝鍦ㄥ悕瀛楀悗闈㈡坊鍔犱竴涓暟瀛楁垨绗﹀彿锛屼互琛ㄧず閲嶅銆?/p>

渚嬪锛?/p>

灏忔槑123

灏忔槑锛?锛?/p>

灏忔槑路閲嶅鐗?/p>

灏忔槑_澶嶅埗鍝?/p>

杩樺彲浠ヤ娇鐢ㄧ壒娈婂瓧绗︽垨emoji鏉ュ垱寤烘洿鍏峰垱鎰忕殑閲嶅缃戝悕銆備緥濡傦細

戋佮己灏忔槑嗉魂

鉁ㄥ皬鏄庘湪

馃寛灏忔槑馃寛

鍙︿竴涓?夋嫨鏄娇鐢ㄢ?滈噸澶嶁?濇垨鈥滐紙閲嶅锛夆?濈瓑鍏抽敭璇嶃?備緥濡傦細

閲嶅鐨勫皬鏄?/p>

灏忔槑锛堥噸澶嶏級

杩樺彲浠ヤ娇鐢ㄧ缉鍐欐垨绠?绉版潵鍒涘缓鏇寸畝娲佺殑閲嶅缃戝悕銆備緥濡傦細

XM123锛堝皬鏄?23锛?/p>

MR锛堝皬绾級

鍙栭噸澶嶇綉鍚嶆椂瑕佹敞鎰忎互涓嬩簨椤癸細

閬垮厤浣跨敤閲嶅澶娆＄殑鏁板瓧鎴栫鍙凤紝鍚﹀垯缃戝悕浼氭樉寰楀啑闀裤??/p>

纭繚缃戝悕涓庝綘鐨勪釜浜鸿祫鏂欐垨鍐呭鐩稿叧銆?/p>

涓嶈浣跨敤鍐掔姱鎬ф垨涓嶆伆褰撶殑閲嶅缃戝悕銆?/p>