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# Creating a DataFrame with random numbers in Pandas

schedule Mar 5, 2023
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PythonPandas
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To create a DataFrame with random numbers in Pandas, use one of NumPy's functions that generate random numbers:

• `np.random.randint(~)` for random integers

• `np.random.default_rng().uniform(~)` for random floats

# DataFrame with random integers

First, we generate a 2 by 3 NumPy array of random integers:

``` arr_random = np.random.randint(low=2, high=10, size=(2,3))arr_random array([[8, 7, 2], [2, 3, 6]]) ```

Here, the lower bound is `2` (inclusive) and the upper bound is `10` (exclusive).

We can then initialise a DataFrame using `arr_random` like so:

``` pd.DataFrame(arr_random, columns=["A","B","C"], index=["a","b"]) A B Ca 4 4 2b 3 7 2 ```

# DataFrame with random floats

First, we generate a 2 by 3 NumPy array of random floats:

``` arr_random = np.random.default_rng().uniform(low=5,high=10,size=[2,3])arr_random array([[7.04518804, 9.09625941, 5.29815702], [7.77653952, 9.22222284, 9.0035309 ]]) ```

Note the following:

• all floats are larger than or equal to 5.

• all floats are less than 10.

To initialise a DataFrame using `arr_random`:

``` pd.DataFrame(arr_random, columns=["A","B","C"]) A B C0 7.927711 5.560577 5.9183311 8.487705 9.111051 9.699249 ```
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