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Detalii evaluare #63429525
Rezumat problemă
#939
Să se scrie un program care citeşte de la tastatura două numere naturale şi determină suma lor.
Candale Silviu (silviu) Detalii
| Problema | sum00 | Operații I/O |
 tastatură/ecran
|
|---|---|---|---|
| Limita timp | 0.1 secunde | Limita memorie |
Total: 64 MB
/
Stivă 8 MB
|
| Id soluție | #63429525 | Utilizator |
Marinescu Luca (LucaD)
|
| Fișier | sum00.cpp | Dimensiune | 2.52 KB |
| Data încărcării | 03 Martie 2026, 11:45 | Scor/rezultat | Eroare de compilare |
Evaluare
Mesaj compilare
sum00.cpp:1:3: error: invalid preprocessing directive #- # -*- coding: utf-8 -*- ^ sum00.cpp:2:3: warning: missing terminating " character [enabled by default] """Untitled0.ipynb ^ sum00.cpp:2:1: error: missing terminating " character """Untitled0.ipynb ^ sum00.cpp:8:3: warning: missing terminating " character [enabled by default] """ ^ sum00.cpp:8:1: error: missing terminating " character """ ^ sum00.cpp:17:23: warning: character constant too long for its type [enabled by default] df_test = pd.read_csv('test.csv') ^ sum00.cpp:18:24: warning: character constant too long for its type [enabled by default] df_train = pd.read_csv('train.csv') ^ sum00.cpp:20:32: warning: character constant too long for its type [enabled by default] df_filtrat = df_train[df_train['native_country'] != 'United-States'] ^ sum00.cpp:20:53: warning: character constant too long for its type [enabled by default] df_filtrat = df_train[df_train['native_country'] != 'United-States'] ^ sum00.cpp:21:36: warning: character constant too long for its type [enabled by default] df_filtrat = df_filtrat[df_filtrat['income'] == '>50K'] ^ sum00.cpp:21:49: warning: multi-character character constant [-Wmultichar] df_filtrat = df_filtrat[df_filtrat['income'] == '>50K'] ^ sum00.cpp:22:16: warning: character constant too long for its type [enabled by default] m = df_filtrat['native_country'].value_counts().to_dict() ^ sum00.cpp:26:32: warning: character constant too long for its type [enabled by default] df_filtrat = df_train[df_train['income'] == '>50K'] ^ sum00.cpp:26:45: warning: multi-character character constant [-Wmultichar] df_filtrat = df_train[df_train['income'] == '>50K'] ^ sum00.cpp:27:16: warning: character constant too long for its type [enabled by default] a = df_filtrat['occupation'].value_counts().to_dict() ^ sum00.cpp:28:14: warning: character constant too long for its type [enabled by default] b = df_train['occupation'].value_counts().to_dict() ^ sum00.cpp:40:9: warning: character constant too long for its type [enabled by default] cols = ['workclass', 'education', 'occupation', 'native_country'] ^ sum00.cpp:40:22: warning: character constant too long for its type [enabled by default] cols = ['workclass', 'education', 'occupation', 'native_country'] ^ sum00.cpp:40:35: warning: character constant too long for its type [enabled by default] cols = ['workclass', 'education', 'occupation', 'native_country'] ^ sum00.cpp:40:49: warning: character constant too long for its type [enabled by default] cols = ['workclass', 'education', 'occupation', 'native_country'] ^ sum00.cpp:43:10: warning: character constant too long for its type [enabled by default] df_train['income'] = le.fit_transform(df_train['income']) ^ sum00.cpp:43:48: warning: character constant too long for its type [enabled by default] df_train['income'] = le.fit_transform(df_train['income']) ^ sum00.cpp:50:36: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:46: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:58: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:74: warning: multi-character character constant [-Wmultichar] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:82: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:92: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:50:115: warning: character constant too long for its type [enabled by default] X_train = df_train.drop(columns = ['income', 'sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:51:20: warning: character constant too long for its type [enabled by default] y_train = df_train['income'] ^ sum00.cpp:52:34: warning: character constant too long for its type [enabled by default] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:52:46: warning: character constant too long for its type [enabled by default] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:52:62: warning: multi-character character constant [-Wmultichar] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:52:70: warning: character constant too long for its type [enabled by default] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:52:80: warning: character constant too long for its type [enabled by default] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:52:103: warning: character constant too long for its type [enabled by default] X_test = df_test.drop(columns = ['sampleid', 'relationship', 'race', 'gender', 'profile_description', 'marital_status']) ^ sum00.cpp:56:9: warning: character constant too long for its type [enabled by default] df_test['Subtask3'] = model.predict(X_test) ^ sum00.cpp:57:9: warning: character constant too long for its type [enabled by default] df_test['Subtask3'] = df_test['Subtask3'].map({ ^ sum00.cpp:57:31: warning: character constant too long for its type [enabled by default] df_test['Subtask3'] = df_test['Subtask3'].map({ ^ sum00.cpp:58:8: warning: character constant too long for its type [enabled by default] 0: '<=50K', ^ sum00.cpp:59:8: warning: multi-character character constant [-Wmultichar] 1: '>50K' ^ sum00.cpp:65:24: warning: character constant too long for its type [enabled by default] df_test2 = pd.read_csv('test.csv') ^ sum00.cpp:66:19: warning: character constant too long for its type [enabled by default] X_test = df_test2['profile_description'] ^ sum00.cpp:68:33: warning: multi-character character constant [-Wmultichar] tf = TfidfVectorizer(analyzer = 'word', ngram_range=(1, 3), stop_words = 'english') ^ sum00.cpp:68:74: warning: character constant too long for its type [enabled by default] tf = TfidfVectorizer(analyzer = 'word', ngram_range=(1, 3), stop_words = 'english') ^ sum00.cpp:73:9: warning: character constant too long for its type [enabled by default] df_test['Subtask4'] = model.labels_ ^ sum00.cpp:74:15: warning: character constant too long for its type [enabled by default] print(df_test['Subtask4']) ^ sum00.cpp:79:5: warning: character constant too long for its type [enabled by default] 'SubtaskID': 1, ^ sum00.cpp:80:5: warning: character constant too long for its type [enabled by default] 'DatapointID': 1, ^ sum00.cpp:81:5: warning: character constant too long for its type [enabled by default] 'answer': p1 ^ sum00.cpp:85:5: warning: character constant too long for its type [enabled by default] 'SubtaskID': 1, ^ sum00.cpp:86:5: warning: character constant too long for its type [enabled by default] 'DatapointID': 1, ^ sum00.cpp:87:5: warning: character constant too long for its type [enabled by default] 'answer': p2 ^ sum00.cpp:93:9: warning: character constant too long for its type [enabled by default] 'SubtaskID': i, ^ sum00.cpp:94:9: warning: character constant too long for its type [enabled by default] 'DatapointID': row['sampleid'], ^ sum00.cpp:94:28: warning: character constant too long for its type [enabled by default] 'DatapointID': row['sampleid'], ^ sum00.cpp:95:9: warning: character constant too long for its type [enabled by default] 'answer': row[f'Subtask{i}'] ^ sum00.cpp:95:24: warning: character constant too long for its type [enabled by default] 'answer': row[f'Subtask{i}'] ^ sum00.cpp:99:18: warning: character constant too long for its type [enabled by default] df_result.to_csv('result.csv', index = False) ^ sum00.cpp:2:1: error: expected unqualified-id before string constant """Untitled0.ipynb ^ sum00.cpp:60:2: error: expected unqualified-id before ')' token }) ^ sum00.cpp:82:2: error: expected unqualified-id before ')' token }) ^ sum00.cpp:88:2: error: expected unqualified-id before ')' token }) ^ sum00.cpp:96:6: error: expected unqualified-id before ')' token }) ^
Cum funcționează evaluarea?
www.pbinfo.ro permite evaluarea a două tipuri de probleme:
- probleme la care rezolvarea presupune scrierea unui program complet
- probleme la care rezolvarea presupune scrierea unei secvențe de program - câteva instrucțiuni, o listă de declarații, una sau mai multe funcții, etc.
Problema sum00 face parte din prima categorie. Soluția propusă de tine va fi evaluată astfel:
- Programul sursă este compilat folosind compilatorul corespunzător. Dacă în urma compilării se obțin erori sau avertismente, acestea sunt afișate în această pagină.
- Dacă programul a fost compilat, executabilul obținut va fi rulat, furnizându-i-se unul sau mai multe seturi de date de intrare, în concordanță cu restricțiile specifice problemei. Pentru fiecare set de date se obține un anumit punctaj, în raport cu corectitudinea soluției tale.
Suma punctajelor acordate pe testele utilizate pentru verificare este 100. Astfel, soluția ta poate obține cel mult 100 de puncte, caz în care se poate considera corectă.