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CodingHours CoffeeCupsPerDay CoffeeTime CodingWithoutCoffee CoffeeType CoffeeSolveBugs Gender Country AgeRange | |
0 8 2 Before coding Yes Caffè latte Sometimes Female Lebanon 18 to 29 | |
1 3 2 Before coding Yes Americano Yes Female Lebanon 30 to 39 | |
2 5 3 While coding No Nescafe Yes Female Lebanon 18 to 29 | |
3 8 2 Before coding No Nescafe Yes Male Lebanon NaN | |
4 10 3 While coding Sometimes Turkish No Male Lebanon 18 to 29 | |
5 8 2 While coding Sometimes Nescafe Yes Male Lebanon 30 to 39 | |
6 5 2 While coding Yes Nescafe Sometimes Male Lebanon NaN | |
7 10 4 Before coding Sometimes Turkish Sometimes Male Lebanon 18 to 29 | |
8 10 2 While coding Yes American Coffee Sometimes Male Lebanon 30 to 39 | |
9 10 2 While coding Yes Nescafe No Male Lebanon 30 to 39 | |
RangeIndex: 100 entries, 0 to 99 | |
Data columns (total 9 columns): | |
CodingHours 100 non-null int64 | |
CoffeeCupsPerDay 100 non-null int64 | |
CoffeeTime 100 non-null object | |
CodingWithoutCoffee 100 non-null object | |
CoffeeType 99 non-null object | |
CoffeeSolveBugs 100 non-null object | |
Gender 100 non-null object | |
Country 100 non-null object | |
AgeRange 98 non-null object | |
dtypes: int64(2), object(7) | |
memory usage: 7.2+ KB | |
None | |
(100, 9) | |
CodingHours CoffeeCupsPerDay | |
count 100.000000 100.000000 | |
mean 6.410000 2.890000 | |
std 2.644205 1.613673 | |
min 1.000000 1.000000 | |
25% 4.000000 2.000000 | |
50% 7.000000 2.500000 | |
75% 8.000000 4.000000 | |
max 10.000000 8.000000 |
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