Datasets:
Number
int64 1
1M
| English
stringlengths 3
73
| French
stringlengths 2
73
| Spanish
stringlengths 3
69
| Tamazight
stringlengths 2
70
|
---|---|---|---|---|
1 | one | un | uno | ⵢⴰⵏ |
2 | two | deux | dos | ⵙⵉⵏ |
3 | three | trois | tres | ⴽⵕⴰⴹ |
4 | four | quatre | cuatro | ⴽⴽⵓⵥ |
5 | five | cinq | cinco | ⵙⵎⵎⵓⵙ |
6 | six | six | seis | ⵚⴹⵉⵚ |
7 | seven | sept | siete | ⵙⴰ |
8 | eight | huit | ocho | ⵜⴰⵎ |
9 | nine | neuf | nueve | ⵜⵥⴰ |
10 | ten | dix | diez | ⵎⵔⴰⵡ |
11 | eleven | onze | once | ⵢⴰⵏ ⴷ ⵎⵔⴰⵡ |
12 | twelve | douze | doce | ⵙⵉⵏ ⴷ ⵎⵔⴰⵡ |
13 | thirteen | treize | trece | ⴽⵕⴰⴹ ⴷ ⵎⵔⴰⵡ |
14 | fourteen | quatorze | catorce | ⴽⴽⵓⵥ ⴷ ⵎⵔⴰⵡ |
15 | fifteen | quinze | quince | ⵙⵎⵎⵓⵙ ⴷ ⵎⵔⴰⵡ |
16 | sixteen | seize | dieciséis | ⵚⴹⵉⵚ ⴷ ⵎⵔⴰⵡ |
17 | seventeen | dix-sept | diecisiete | ⵙⴰ ⴷ ⵎⵔⴰⵡ |
18 | eighteen | dix-huit | dieciocho | ⵜⴰⵎ ⴷ ⵎⵔⴰⵡ |
19 | nineteen | dix-neuf | diecinueve | ⵜⵥⴰ ⴷ ⵎⵔⴰⵡ |
20 | twenty | vingt | veinte | ⵙⵉⵎⵔⴰⵡ |
21 | twenty-one | vingt et un | veintiuno | ⵙⵉⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
22 | twenty-two | vingt-deux | veintidós | ⵙⵉⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
23 | twenty-three | vingt-trois | veintitrés | ⵙⵉⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
24 | twenty-four | vingt-quatre | veinticuatro | ⵙⵉⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
25 | twenty-five | vingt-cinq | veinticinco | ⵙⵉⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
26 | twenty-six | vingt-six | veintiséis | ⵙⵉⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
27 | twenty-seven | vingt-sept | veintisiete | ⵙⵉⵎⵔⴰⵡ ⴷ ⵙⴰ |
28 | twenty-eight | vingt-huit | veintiocho | ⵙⵉⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
29 | twenty-nine | vingt-neuf | veintinueve | ⵙⵉⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
30 | thirty | trente | treinta | ⴽⵕⴰⵎⵔⴰⵡ |
31 | thirty-one | trente et un | treinta y uno | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
32 | thirty-two | trente-deux | treinta y dos | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
33 | thirty-three | trente-trois | treinta y tres | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
34 | thirty-four | trente-quatre | treinta y cuatro | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
35 | thirty-five | trente-cinq | treinta y cinco | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
36 | thirty-six | trente-six | treinta y seis | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
37 | thirty-seven | trente-sept | treinta y siete | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵙⴰ |
38 | thirty-eight | trente-huit | treinta y ocho | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
39 | thirty-nine | trente-neuf | treinta y nueve | ⴽⵕⴰⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
40 | forty | quarante | cuarenta | ⴽⴽⵓⵥⵎⵔⴰⵡ |
41 | forty-one | quarante et un | cuarenta y uno | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
42 | forty-two | quarante-deux | cuarenta y dos | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
43 | forty-three | quarante-trois | cuarenta y tres | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
44 | forty-four | quarante-quatre | cuarenta y cuatro | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
45 | forty-five | quarante-cinq | cuarenta y cinco | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
46 | forty-six | quarante-six | cuarenta y seis | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
47 | forty-seven | quarante-sept | cuarenta y siete | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵙⴰ |
48 | forty-eight | quarante-huit | cuarenta y ocho | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
49 | forty-nine | quarante-neuf | cuarenta y nueve | ⴽⴽⵓⵥⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
50 | fifty | cinquante | cincuenta | ⵙⵎⵎⵓⵎⵔⴰⵡ |
51 | fifty-one | cinquante et un | cincuenta y uno | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
52 | fifty-two | cinquante-deux | cincuenta y dos | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
53 | fifty-three | cinquante-trois | cincuenta y tres | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
54 | fifty-four | cinquante-quatre | cincuenta y cuatro | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
55 | fifty-five | cinquante-cinq | cincuenta y cinco | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
56 | fifty-six | cinquante-six | cincuenta y seis | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
57 | fifty-seven | cinquante-sept | cincuenta y siete | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵙⴰ |
58 | fifty-eight | cinquante-huit | cincuenta y ocho | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
59 | fifty-nine | cinquante-neuf | cincuenta y nueve | ⵙⵎⵎⵓⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
60 | sixty | soixante | sesenta | ⵚⴹⵉⵎⵔⴰⵡ |
61 | sixty-one | soixante et un | sesenta y uno | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
62 | sixty-two | soixante-deux | sesenta y dos | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
63 | sixty-three | soixante-trois | sesenta y tres | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
64 | sixty-four | soixante-quatre | sesenta y cuatro | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
65 | sixty-five | soixante-cinq | sesenta y cinco | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
66 | sixty-six | soixante-six | sesenta y seis | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
67 | sixty-seven | soixante-sept | sesenta y siete | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵙⴰ |
68 | sixty-eight | soixante-huit | sesenta y ocho | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
69 | sixty-nine | soixante-neuf | sesenta y nueve | ⵚⴹⵉⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
70 | seventy | soixante-dix | setenta | ⵙⴰⵎⵔⴰⵡ |
71 | seventy-one | soixante et onze | setenta y uno | ⵙⴰⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
72 | seventy-two | soixante-douze | setenta y dos | ⵙⴰⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
73 | seventy-three | soixante-treize | setenta y tres | ⵙⴰⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
74 | seventy-four | soixante-quatorze | setenta y cuatro | ⵙⴰⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
75 | seventy-five | soixante-quinze | setenta y cinco | ⵙⴰⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
76 | seventy-six | soixante-seize | setenta y seis | ⵙⴰⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
77 | seventy-seven | soixante-dix-sept | setenta y siete | ⵙⴰⵎⵔⴰⵡ ⴷ ⵙⴰ |
78 | seventy-eight | soixante-dix-huit | setenta y ocho | ⵙⴰⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
79 | seventy-nine | soixante-dix-neuf | setenta y nueve | ⵙⴰⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
80 | eighty | quatre-vingts | ochenta | ⵜⴰⵎⵎⵔⴰⵡ |
81 | eighty-one | quatre-vingt-un | ochenta y uno | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
82 | eighty-two | quatre-vingt-deux | ochenta y dos | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
83 | eighty-three | quatre-vingt-trois | ochenta y tres | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
84 | eighty-four | quatre-vingt-quatre | ochenta y cuatro | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
85 | eighty-five | quatre-vingt-cinq | ochenta y cinco | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
86 | eighty-six | quatre-vingt-six | ochenta y seis | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
87 | eighty-seven | quatre-vingt-sept | ochenta y siete | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵙⴰ |
88 | eighty-eight | quatre-vingt-huit | ochenta y ocho | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
89 | eighty-nine | quatre-vingt-neuf | ochenta y nueve | ⵜⴰⵎⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
90 | ninety | quatre-vingt-dix | noventa | ⵜⵥⴰⵎⵔⴰⵡ |
91 | ninety-one | quatre-vingt-onze | noventa y uno | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵢⴰⵏ |
92 | ninety-two | quatre-vingt-douze | noventa y dos | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵙⵉⵏ |
93 | ninety-three | quatre-vingt-treize | noventa y tres | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⴽⵕⴰⴹ |
94 | ninety-four | quatre-vingt-quatorze | noventa y cuatro | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⴽⴽⵓⵥ |
95 | ninety-five | quatre-vingt-quinze | noventa y cinco | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵙⵎⵎⵓⵙ |
96 | ninety-six | quatre-vingt-seize | noventa y seis | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵚⴹⵉⵚ |
97 | ninety-seven | quatre-vingt-dix-sept | noventa y siete | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵙⴰ |
98 | ninety-eight | quatre-vingt-dix-huit | noventa y ocho | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵜⴰⵎ |
99 | ninety-nine | quatre-vingt-dix-neuf | noventa y nueve | ⵜⵥⴰⵎⵔⴰⵡ ⴷ ⵜⵥⴰ |
100 | one hundred | cent | cien | ⵜⵉⵎⵉⴹⵉ |
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Tamazight Numbers Dataset
Dataset Description
This dataset contains numbers from 1 to 1,000,000 translated into:
- English.
- French.
- Spanish.
- Tamazight (Berber).
The dataset is designed to assist researchers and developers in building machine learning models for understanding and converting numbers into words in multiple languages.
Dataset Structure
The dataset contains the following columns:
Column | Description | Example |
---|---|---|
Number | The numeric representation | 1 |
English | English translation of the number | one |
French | French translation of the number | un |
Spanish | Spanish translation of the number | uno |
Tamazight | Tamazight translation of the number | ⵢⴰⵏ |
How to Use the Dataset
This dataset can be used to train machine learning models for:
- Converting numbers to words.
- Translating between languages.
- Understanding linguistic structures of numbers.
Example:
import pandas as pd
# Load the dataset
df = pd.read_csv("Numbers: Multilingual - Tamazight (1 to 1M).tsv", sep="\t")
# Display the first 5 rows
print(df.head())
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