Reformat Date - Practice Coding Problems

Reformat Date - Problem

String Easy

Given a date string in the form Day Month Year, convert it to the format YYYY-MM-DD.

Input Format:

Day is in the set {"1st", "2nd", "3rd", "4th", ..., "30th", "31st"}
Month is in the set {"Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"}
Year is in the range [1900, 2100]

Output Format:

YYYY denotes the 4-digit year
MM denotes the 2-digit month (01-12)
DD denotes the 2-digit day (01-31)

Input & Output

Example 1 — Basic Case

$ Input: date = "20th Oct 2052"

› Output: "2052-10-20"

💡 Note: Split into day=20th, month=Oct, year=2052. Remove 'th' to get day=20, Oct is month 10, format as 2052-10-20

Example 2 — Single Digit Day

$ Input: date = "6th Jun 1933"

› Output: "1933-06-06"

💡 Note: Day 6th becomes 06, Jun is month 06, year 1933. Result: 1933-06-06 with zero padding

Example 3 — End of Year

$ Input: date = "31st Dec 2099"

› Output: "2099-12-31"

💡 Note: Last day of year: 31st becomes 31, Dec is month 12, format as 2099-12-31

Constraints

Date string is always valid and in the format "Day Month Year"
Day is in the set {"1st", "2nd", "3rd", ..., "31st"}
Month is in the set {"Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"}
Year is in the range [1900, 2100]

Visualization

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Understanding the Visualization

Input

Human-readable date: "20th Oct 2052"

Process

Split components and convert: day=20, Oct→10, year=2052

Output

ISO format with padding: "2052-10-20"

Key Takeaway

🎯 Key Insight: Parse each date component separately and use hash map for efficient month name to number conversion

Asked in

a Amazon 15 M Microsoft 12 f Facebook 8

The key insight is to split the date string, extract numeric values, and use a hash map for efficient month lookup. Best approach uses hash map for O(1) month conversion. Time: O(1), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ String Splitting with Linear Month Search	O(1)	O(1)	Split the date string and search for month name linearly
Hash Map Lookup	O(1)	O(1)	Use a hash map for O(1) month name to number conversion

String Splitting with Linear Month Search — Algorithm Steps

Split input string by spaces
Extract numeric day by removing suffix
Find month number by linear search
Format as YYYY-MM-DD with zero padding

Visualization

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Step-by-Step Walkthrough

Split Input

Break "20th Oct 2052" into ["20th", "Oct", "2052"]

Process Components

Extract day=20, search for Oct in months array, year=2052

Format Output

Combine as "2052-10-20" with zero padding

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

char* solution(char* date) {
    char dayStr[10], monthStr[10], yearStr[10];
    sscanf(date, "%s %s %s", dayStr, monthStr, yearStr);
    
    // Extract day number (remove ordinal suffix)
    dayStr[strlen(dayStr)-2] = '\0';
    int day = atoi(dayStr);
    
    // Map month to number (linear search)
    char* months[] = {"Jan", "Feb", "Mar", "Apr", "May", "Jun",
                     "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"};
    int month = 0;
    for (int i = 0; i < 12; i++) {
        if (strcmp(months[i], monthStr) == 0) {
            month = i + 1;
            break;
        }
    }
    
    int year = atoi(yearStr);
    
    char* result = (char*)malloc(11 * sizeof(char));
    sprintf(result, "%04d-%02d-%02d", year, month, day);
    return result;
}

int main() {
    char date[100];
    fgets(date, sizeof(date), stdin);
    date[strcspn(date, "\n")] = 0;
    
    char* result = solution(date);
    printf("%s\n", result);
    free(result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(1)

Fixed operations: split (3 parts), strip suffix, linear search through 12 months

✓ Linear Growth

Space Complexity

O(1)

Only stores a few string variables, no extra data structures

✓ Linear Space

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Smart Actions

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

String Splitting with Linear Month Search — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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