To count the unique values of columns in a pandas DataFrame or unique values of a Series, the simplest way is to use the pandas **nunique()** function.

`unique_values = df["variable"].nunique()`

When working with data, it’s important to be able to find the basic descriptive statistics of a set of data.

One such piece of information which could be important is the count of unique values in a dataset.

To count unique values in a DataFrame, we can use the pandas nunique() function.

The following code will get you the count of unique values of a single column in Python:

`unique_values = df["variable"].nunique()`

If you want to count the unique values of an entire DataFrame in pandas, you can call **nunique()** in the following way:

`unique_values = df.nunique()`

## Count Unique Values in All Columns of DataFrame Using Pandas

Let’s say I have the following pandas DataFrame:

```
Name Weight_Change Month
0 Jim -16.20 1
1 Sally 12.81 1
2 Bob -20.45 1
3 Sue 15.35 1
4 Jill -12.43 1
5 Larry -18.52 1
6 Jim -6.10 2
7 Sally -2.81 2
8 Bob 12.45 2
9 Sue -0.32 2
10 Jill -1.23 2
11 Larry -8.52 2
12 Jim 5.20 3
13 Sally 12.81 3
14 Bob -2.45 3
15 Sue 5.35 3
16 Jill -2.43 3
17 Larry -1.85 3
```

We can call the **nunique** function on the DataFrame to get the number of unique values for all of the columns.

Below shows a simple example of how you can use **nunique()** to get the count of the unique values for all of the columns in Python.

```
print(df.nunique())
Name 6
Weight_Change 18
Month 3
dtype: int64
```

## Count Unique Values of Single Column Using Pandas

Let’s say we only want to get the count of unique values of a single column in a pandas DataFrame.

In the DataFrame above, let’s get the count of unique values for the column “Month”. We should expect 3, respectively.

To get the count of unique values of the a single column, you can do the following in your Python code:

```
print(df["Month"].nunique())
#Output:
3
```

If you want to get the count of unique values for multiple columns, you can do the following.

In the DataFrame above, let’s get the count of unique values for the columns “Month” and “Name”. We should expect 3 and 6, respectively.

To get the count of unique values of the two columns, you can do the following in your Python code:

```
print(df[["Month", "Name"]].nunique())
#Output:
3
6
dtype: int64
```

Hopefully this article has been useful for you to get the count of unique values in a pandas DataFrame using Python.

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