random number generator with exclusions

Random Number Generator

Pick a number - how to use the random number generator., possible applications of the random number picker, what is rng, and how do random number generators work, true random number generators and pseudorandom number generators.

This random number generator can produce pseudorandom numbers within a given range. You can pick numbers from -999,999,999,999,999 to 999,999,999,999,999, choose to generate decimals or integers, include or exclude the minimum and maximum values, disallow duplicates (random number generator with no repeats), and sort results from smallest to largest.

It can serve as a single random number picker or a random number list generator . In the text below, you'll find information on how to use this random sequence generator. It will also answer the questions: "what is RNG?", "what is the difference between pseudorandom number generators and true random number generators?" and "how do random number generators work?"

The numbers generated by this lucky number generator are pseudorandom - not truly random, but suitable for most purposes. However, be careful if you want to use it to encrypt top-secret government documents.

Single random number generator

If you want to generate one random number, choose a number that will be the lower limit (the minimum value), and then pick a number that will be the upper limit (the maximum value). To generate again, click the arrow below the "Result" field. (Make sure the "autosave" option is turned on by clicking the floppy disk icon next to the "Minimum value" and "Maximum value" fields).

By default, minimum and maximum values are included in the range of numbers generated. If you want to exclude them, click "advanced mode" (below the "Result" field), and you'll see the option to exclude one or both.

You can also generate decimals (up to two decimal places) - to do that change the "type of number(s)" setting.

Random number list generator

If you choose the "multiple numbers" option in the "Generate" field, input how many numbers you need, and you'll see a sequence of random numbers.

In the advanced mode, you can also choose whether you want to allow duplicates in the random list and whether you want the results to be sorted (from smallest to largest).

If you want to generate numbers with the same settings again, click the "autosave" option to the right of the variables you want to stay the same.

Here are some ways you can use the random number generator. It may be helpful if you need the following:

a random number list generator (random number table generator)

Choose the "multiple numbers" option and input how many numbers you need (the list's length).

a phone number generator

Choose the "multiple numbers," enter "7" into the "how many" field (or another adequate number if you're not in the USA), and set the minimum value to 0 and the maximum value to 9. If 0 is the first number of the sequence, try again. The sequence will be a random phone number.

a random 4-digit number generator

Set the minimum value to 1,000 and the maximum value to 9,999.

a random number sequence generator

Works the same as a random list generator; see above.

a random number generator no repeats

If you generate multiple numbers and want no repeats, go to advanced mode and set "no" in the "allow duplicates" section.

to pick a random number between 69 and 666

Set the minimum value to 69 and the maximum value to 666. RNGesus will forgive you. 😈

to choose a random number between 1 and 4

Set the minimum value to 1 and the maximum value to 4.

to generate 5 random numbers

Choose "multiple numbers" in the first field and enter "5" in the "how many" field.

to pick a number from 1 to 10

Set the minimum value to 1 and the maximum value to 10.

RNG (random number generator) is a device that produces a sequence of numbers that can't be predicted (each outcome has the same probability of being chosen).

Rolling dice is a random hardware number-generating method (and our dice probability calculator is its analog version). Each result has the same chance of appearing ( P = 1/6 ). The same goes for flipping a coin - in our coin flip probability calculator , you can calculate the probability of getting heads and figure it's equal to 50%, and so is the probability of getting tails (not including the possibility of it landing on its side). If you're curious enough, you can try flipping a coin 100 times to check that the longer you flip, the closer you get to an even distribution of outcomes. This phenomenon is known as the law of large numbers.

Although rolling dice is fun, using a software is much quicker and more convenient. But how can computers produce random results if they're entirely deterministic? All that computers do is follow instructions, so how can anything they do be random?

One solution is relying on some external input, which is truly random. For example, computers can use data from a piece of hardware that measures a random physical phenomenon like background radiation. These types of devices are called true random number generators.

Another way is to produce an outcome that seems unpredictable but, in fact, is the result of a strictly defined mathematical process. Software that does this is called a pseudorandom number generator . It takes in a "random enough" number (a seed), e.g., a part of the current time in the system's clock, and performs a function on it. The result is a pseudorandom number.

For many purposes (like gameplay or graphics), pseudorandom generators are enough, but true random number generators are needed especially for encryption.

This number generator is pseudorandom and uses the JavaScript function Math.random(). The algorithm which produces the result depends on the web browser you use. Nowadays, most browsers use the xorshift128+ algorithm, which is based on bitwise operations, which are manipulation of data at the level (learn what a bit is in our byte conversion tool)

What does RNG mean?

RNG stands for random number generator. It is an algorithm that produces a sequence of numbers that can't be predicted, so each outcome has the same probability of being chosen.

We distinguish between true random number generators (TRNG) and pseudorandom number generators (PRGN). PRNG are often used in computer games while TRNG are used for encryption.

How do random number generators work?

There are two main principles to generate random numbers:

• True random number generator algorithms take the current value of a physical environmental attribute that is constantly changing in a way that is practically impossible to model.
• Pseudorandom number generator algorithms reproduce numbers by taking a seed as an input and performing a precisely defined algorithm on it.

What is a pseudorandom number?

A pseudorandom number is an outcome that seems unpredictable but, in fact, is the result of a strictly defined mathematical process. The algorithms of pseudorandom number generators (PRGN) take a seed to create random numbers. They are used widely in simulations, computer programming, and as long as the seed stays a secret, also in cryptography.

How to generate a new phone number?

To generate a new phone number:

• In the random number generator, choose the adequate number of digits for a phone number of your desired country (7 digits for USA).
• Set the minimum value to 0 and the maximum value to 9.
• If 0 is the first number of the sequence, let the generator run again.
• The resulting sequence will be a random phone number.

How to generate a random number in Python?

There are many ways to generate a pseudorandom number or sequence in Python. Here are some useful ones:

• random.randint(a, b) generates random integers;
• random.random(a, b) generates floating point numbers; and
• random.sample(a, b, length_of_list) generates sequences of random numbers.

Consult Python's documentation for more functions in the random module.

Beware: Python uses the Mersenne Twister algorithm as its default PRNG. It is completely unsuitable for cryptographic purposes because its seeds are predictable.

Polynomial regression

Significant figures.

• Biology ( 97 )
• Chemistry ( 94 )
• Construction ( 139 )
• Conversion ( 257 )
• Ecology ( 27 )
• Everyday life ( 251 )
• Finance ( 549 )
• Food ( 65 )
• Health ( 436 )
• Math ( 656 )
• Physics ( 497 )
• Sports ( 101 )
• Statistics ( 182 )
• Other ( 171 )
• Discover Omni ( 40 )

Random Number Generator

This version of the generator creates a random integer. It can deal with very large integers up to a few thousand digits.

Comprehensive Version

This version of the generator can create one or many random integers or decimals. It can deal with very large numbers with up to 999 digits of precision.

A random number is a number chosen from a pool of limited or unlimited numbers that has no discernible pattern for prediction. The pool of numbers is almost always independent from each other. However, the pool of numbers may follow a specific distribution. For example, the height of the students in a school tends to follow a normal distribution around the median height. If the height of a student is picked at random, the picked number has a higher chance to be closer to the median height than being classified as very tall or very short. The random number generators above assume that the numbers generated are independent of each other, and will be evenly spread across the whole range of possible values.

A random number generator, like the ones above, is a device that can generate one or many random numbers within a defined scope. Random number generators can be hardware based or pseudo-random number generators. Hardware based random-number generators can involve the use of a dice, a coin for flipping, or many other devices.

A pseudo-random number generator is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. Computer based random number generators are almost always pseudo-random number generators. Yet, the numbers generated by pseudo-random number generators are not truly random. Likewise, our generators above are also pseudo-random number generators. The random numbers generated are sufficient for most applications yet they should not be used for cryptographic purposes. True random numbers are based on physical phenomena such as atmospheric noise, thermal noise, and other quantum phenomena. Methods that generate true random numbers also involve compensating for potential biases caused by the measurement process.

• Comment Picker Instagram
• Comment Picker Facebook
• Comment Picker X
• Comment Picker YouTube
• Current language of site: EN (English)
• NL (Nederlands)

Random Number Generator

Pick a number or generate a sequence of random numbers.

Ad-free & Premium features? Go Premium >

Number Generator

Random Number Generator is an online tool where you can easily pick a number or generate sequences of (unique) random numbers.

By default, the tool generates one random number from 1 to 10.

Change the settings of the number generator to generate multiple numbers or sequences. You can also choose if you want to use only unique numbers or exclude numbers.

Ad-free, Premium features & limits, and more.

Tip: Do you prefer to select a number by spinning a wheel of numbers? Try the Number Picker Wheel .

Number Picker Settings

Leave default number generator settings to pick a number between 1 and 10.

Random number

How to pick a number.

You can pick a random number in the following steps:

• Select number range.
• Select number & sequence settings.
• Select number output settings.
• Press Generate random number.
• Share, copy, export or print numbers.

Do you want to pick a letter of generate a list of random letters? Try the Random Letter Generator .

What is a Random Number Generator?

Random Number Generator or Number Picker is a free online tool where you can pick a number or a sequence of random numbers. You can generate a list with unique random numbers with no repeats and choose to exclude numbers.

You can adjust multiple settings in the to customize the numbers possible, amount of numbers and sequences, output of numbers, and more.

Random Number Picker

A Number Picker is used for many use cases, such as:

• Pick a number game.
• Number Randomizer.
• Alternative for a Dice Roller .
• Learning kids numbers and counting.
• To generate lottery or bingo numbers.

You can generate a random number between 1 or 2 or from 1 to 3, 1 to 10, 1 to 50, 1 to 100, up to 1.000.000.000 and everything in between. So yes, everything is possible with our Number Picker.

Random Number Sequence Generator

It's possible to generate sequences of numbers by changing the amount of number sequences. You will get multiple list of numbers that can be used. You can generate up to 100 number sequences with each 1000 numbers.

Example of the results of the Number Generator with 5 number sequences selected with each 10 random numbers between 1 and 100.

Google Number Generator

Why should I use your Number Generator instead of the Google Random Number Generator?

5 reasons why our tool is better:

• You can pick up to 1000 random numbers.
• Possibility to exclude numbers.
• Generate multiple sequences of random numbers at once.
• Option to generate a list with unique random numbers.
• Easy to export print, copy or share the random numbers.

If you have any tips, feedback or improvements for our Number Generator to make it even better, please send a message via Facebook or Instagram .

Number Generator settings

Leaving the default settings will generate a random number between 1 and 10. If you want advanced settings, you can change the default options. We will explain all settings of the Number Generator.

Number range

You can change the minimum and maximum number which are possible to generate. You can enter negative numbers as well. By default, the min number is 1 and max number is 10. The maximum number you can generate us 1.000.000.000.

You can press on of the buttons in the settings to quickly change to number range.

Amount of numbers & sequences

The amount of number is related to one sequence and can be maximum of 1000 numbers per sequence. You can generate up to 100 number sequences at once. Each sequence is generated apart from each other, so it will not take the previous number sequence into account. If you select 2 number sequences, you might get the same random numbers.

Exclude numbers

You can enter numbers in this field separated by comma which you want to exclude in the sequence of random numbers. Any number that is entered in this field will never be generated in any sequence. Make sure excluded numbers are in between the minimal and maximum value, otherwise it will be ignored.

Unique numbers in sequence (no repeat)

If you enable this option, it will only generate unique numbers is a number sequence.It won't be possible to have 2 the equal numbers in a sequence. A number can appear multiple times in different sequences. If there are no numbers possible anymore, you might end up with less numbers then selected in the amount of numbers.

Frequently Asked Questions

You can find answers of frequently asked questions about our tool in the list below. Is your specific question not in the list? Please send us a message via Facebook or Instagram.

The Random Number Generator is using a pseudorandom number generator (PRNG) for randomness. Each number in each number sequence will be randomly chosen using this method.

The maximum number that you can choose in the Number generator is 1.000.000.000 (1 billion). The minimum number is set to 0, however it is also possible to use negative numbers.

You can use the Random Number Generator for free without any limits.

You can generate a set from 1 to 1000 random numbers in a number sequence. You can generate up to 100 number sequences each time. If you use the unique numbers filter, the maximum amount of numbers will be the maximum possible numbers between the minimum and maximum value.

You can exclude any number that is in between the minimum and maximum number in the Number Generator settings. Each number that you want to exclude should be separated by a comma.

Yes, you are able to export the random numbers to Excel in CSV format. You are also able to share, copy or print list of random numbers.

We don't have a native mobile app, but our website is 100% mobile friendly. You can save and bookmark or add our website to your home screen to quickly access the Number Generator app.

Random Generator Tools

• Random Number Generator Wheel Go to Random Number Generator Wheel tool ⇒
• Random Letter Generator Go to Random Letter Generator tool ⇒
• Lottery Number Generator Go to Lottery Number Generator tool ⇒
• Random Word Generator Go to Random Word Generator tool ⇒
• Random Team Generator Go to Random Team Generator tool ⇒
• Combination Generator Go to Combination Generator tool ⇒

We know: Ads are annoying. But Ads helps us to cover costs and to keep tools free.

So, you can add us to your ad blocker's whitelist or join Premium for an 100% Ad-free website.

Thanks for your support. We really appreciate it.

Join Premium >

Random Numbers:

Random number generator.

Its the core of all randomness. Pick a number or generate a whole sequence of numbers within a minimum and maximum value (inclusive) while including or suppress duplicates. Your device is used to quickly generate these numbers, completely random and unique to you every time.

Change the quantity to one if you just want it to pick a number.

You can switch the presentation to roll some dice instead. Or change gears completely with the phone number generator or random letter generator .

Random Number Generator 🎲

Use this random generator to get a truly random, cryptographically safe number. It generates random numbers (with no repeats, or with repeats) that can be used where unbiased randomization is needed such as when drawing numbers for a lottery, raffle, giveaway, or sweepstake. An RNG draw can also be used for determining who goes first in a game, and so on.

    Generation result

Related calculators.

• How to pick a random number between two numbers?
• Where are random numbers useful?
• Generating a random number

Sources of randomness

• True random versus pseudo random number generators

    How to pick a random number between two numbers?

You can use this random number generator to pick a truly random number between any two numbers. For example, to get a random number between 1 and 10 , including 10, enter 1 in the first field and 10 in the second, then press "Get Random Number". Our randomizer will pick a number from 1 through 10 at random. To generate a random number between 1 and 100, do the same, but with 100 in the second field of the picker.

To simulate a dice roll , the range should be 1 to 6 for a standard six-sided dice. To perform the equivalent of a coin flip , set the range between 1 and 2 and the random selector will pick a number between 1 and 2.

To generate more than one random number from a min-max range , just select how many you need from the drop-down below. To generate unique numbers with no repeats, leave the "no repeats" checkbox on. For example, selecting to draw 6 numbers out of the set of 1 to 49 possible would be equivalent to simulating a lottery draw for a game with these parameters. If you want numbers with repeats, just flip the "no repeats" checkbox to its off state and the same number may be drawn repeatedly by chance.

    Where are random numbers useful?

You might be organizing a charity lottery , a giveaway, a raffle, a sweepstakes, etc. and you need to draw a winner - this generator is for you! It is completely unbiased and outside of your control , so you can assure your crowd of the fairness of the draw, which might not be true if you are using standard methods like rolling a dice. If you need to choose several among the participants instead, just select the number of unique numbers you want generated by our random number picker and you are all set. However, it is usually best to draw the winners one after another, to keep the tension for longer (discarding repeat draws as you go).

A random number generator is also useful if you need to decide who goes first in some game or activity, such as board games, sport games and sports competitions. The same is true if you need to decide the participation order for multiple players / participants. Picking a team at random or randomizing a list of participants also depends on randomness.

Nowadays, a number of government-run and private lotteries and lottery games are using software RNGs to pick a number instead of more traditional drawing methods. RNGs are also used to determine the outcomes of all modern slot machines. For some other modern applications, see How Random Numbers Are the Driving Force Behind Video Games, Jury Selection, and More .

Finally, random numbers are also useful in statistics and simulations. In statistical applications one often needs to draw numbers randomly from distributions different than the uniform, e.g. a normal distribution, binomial distribution, power distribution, pareto distribution... For such use-cases a more sophisticated software is required to perform the draw.

    Generating a random number

There is a philosophical question about what exactly "random" is , but its defining characteristic is surely unpredictability . We cannot talk about the unpredictability of a single number, since that number is just what it is, but we can talk about the unpredictability of a series of numbers (number sequence). If a sequence of numbers is random, then you should not be able to predict the next number in the sequence while knowing any part of the sequence so far. Examples for this are found in rolling a fair dice, spinning a well-balanced roulette wheel, drawing balls from a sphere, and the classic flip of a coin . No matter how many dice rolls, coin flips, roulette spins or lottery draws you observe, you do not improve your chances of guessing the next number in the sequence. For those interested in physics the classic example of random movement is the Browning motion of gas or fluid particles.

Given the above and knowing that computers are fully deterministic, meaning that their output is completely determined by their input, one might say that we cannot generate a random number with a computer. However, one will only partially be correct, since a dice roll or a coin flip is also deterministic, if you know the state of the system.

The randomness in our number generator comes from physical processes - our server gathers environmental noise from device drivers and other sources into an entropy pool , from which random numbers are created [1] .

According to Alzhrani & Aljaedi [2] there are four sources of randomness that are used in the seeding of a generator of random numbers, two of which are used in our number picker:

• Entropy from the disk when the drivers call it - gathering seek time of block layer request events.
• Interrupt events from USB and other device drivers
• System values such as MAC addresses, serial numbers and Real Time Clock - used only to initialize the input pool, mostly on embedded systems.
• Entropy from input hardware - mouse and keyboard actions (not used)

This puts the RNG we use in this randomizer in compliance with the recommendations of RFC 4086 on randomness required for security [3] .

    True random versus pseudo random number generators

A pseudo-random number generator (PRNG) is a finite state machine with an initial value called the seed [4] . Upon each request to draw a number at random, a transaction function computes the next internal state and an output function produces the actual number based on the state. A PRNG deterministically produces a periodic sequence of values that depends only on the initial seed given. An example would be a linear congruential generator like PM88. Thus, knowing even a short sequence of generated values it is possible to figure out the seed that was used and thus - know the next value.

A cryptographic pseudo-random number generator (CPRNG) is a PRNG in that it is predictable if the internal state is known. However, assuming the generator was seeded with sufficient entropy and the algorithms have the needed properties, such generators will not quickly reveal significant amounts of their internal state, meaning that you would need a huge amount of output before you can mount a successful attack on them. Randomizers of this type are suitable if the number drawing generator is to be used in a high stakes situation.

A hardware RNG is based on an unpredictable physical phenomenon, referred to as "entropy source" . Radioactive decay , or more precisely the points in time at which a radioactive source decays is a phenomenon as close to randomness as we know, while decaying particles are easy to detect. Another example is heat variation - some Intel CPUs have a detector for thermal noise in the silicon of the chip that outputs random numbers.

Hardware RNGs are, however, often biased and, more importantly, limited in their capacity to generate sufficient entropy in practical spans of time, due to the low variability of the natural phenomenon sampled. Thus, another type of RNG is needed for practical applications: a true random number generator (TRNG). In it cascades of hardware RNGs (entropy harvester) are used to periodically reseed a PRNG. When the entropy is sufficient, it behaves as a TRNG. This is the type of process used to generate random numbers in this tool.

    References

1 Linux manual page on "urandom"

2 Alzhrani K., Aljaedi A. (2015) "Windows and Linux Random Number Generation Process: A Comparative Analysis", International Journal of Computer Applications 113:21

3 Schiller J., Crocker S. (2005) "IETF RFC 4086 - Randomness Requirements for Security"

4 Goichon F., Lauradoux C., Salagnac G., Vuillemin T. (2012) "A study of entropy transfers in the Linux Random Number Generator", research report 8060

Cite this calculator & page

If you'd like to cite this online calculator resource and information as provided on the page, you can use the following citation: Georgiev G.Z., "Random Number Generator" , [online] Available at: https://www.gigacalculator.com/calculators/random-number-generator.php URL [Accessed Date: 03 Nov, 2023].

     Statistical calculators

Features of this random number generator:

• Generate sequence using a loop
• Speed loop that lets you control the speed of random generation
• History of generated numbers for both the sequence and the loop
• Copy numbers to clipboard
• Delete or Copy History
• Create favorite random number generators
• Remembers recently used random number generators
• Remembers last generated number
• Use Seed for a Seeded RNG to generate the same sequence again
• Reset Seed per session or remember the seed for longer
• Option to allow numbers to repeat in the loop or the sequence
• Notifies when all numbers in the sequence are generated
• Auto-stop loop when it has looped through the range of numbers
• Exclude specific numbers from the list
• Select odd, even or half for games
• Show total sum of the random numbers
• Specific shortcuts for single digit ranges, pin codes, lottery, dice and coins
• Lucky touch screen that allows you to select lucky numbers using your touch
• Multiple screens for easy access of presets

Random Number Generator App in Playstore

Random Numbers with Exclusions

I have a random number generator set up to randomly pick an element off of the Periodic Table as shown below:

r=randomGenerator()

AtomicNumber = r.int(1,118)

Is there a way I can exclude sets of element? For example, can I exclude numbers 21-30 and 39-48 in this rand. num. generator?

A little easier in a graph (which you could just hide)

If you don’t use the n to “seed” the list, students will all have the same random element.

The code is not liking the brackets. Here is the activity: Ions Practice • Activity Builder by Desmos

The PeriodicInfo “graph” is where all of the content is located.

Slides 1-4 have different domains, like (1,20) or (31,38) for example. Slide 5 is where I tried to implement the code you suggested, but no luck.

That code works in the actual graph, not the CL for the graph.

If you have a spreadsheet of the elements you want and their corresponding values (here’s one I found online), you can copy/paste numeric values into a table in a Desmos graph. Then, if you just choose a random number from (1…length(List)), you could just reference that element from each attribute.

Here’s an example using 1-20 from the linked spreadsheet (I hid columns with nonnumeric data):

Oh wow, thank you for this!

I’m still new to the CL and am not super familiar with how useful the graph can be. I struggle going back and forth between the two.

You can’t manipulate lists with the CL, and generally calculations are easier in graphs.

One big thing that CL can do that the graphs can’t is randomize for each student. That’s why in my original example you’d define n in the CL, because it would be different for each student. Using that value to “seed” your lists in your graphs makes them unique for each student, when they wouldn’t be otherwise.

Gotcha. That makes sense. I also discovered that clicking the “Play” button would randomized the number on consecutive slides. Found that out after my student kept getting the same problem 10x in a row!