# How can I get descriptive statistics of a NumPy array?

Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about How can I get descriptive statistics of a NumPy array in Python. So Here I am Explain to you all the possible Methods here.

## How can I get descriptive statistics of a NumPy array?

1. How can I get descriptive statistics of a NumPy array?

This is not a pretty solution, but it gets the job done. The problem is that by specifying multiple dtypes, you are essentially making a 1D-array of tuples (actually `np.void`), which cannot be described by stats as it includes multiple different types, incl. strings.

2. get descriptive statistics of a NumPy array

This is not a pretty solution, but it gets the job done. The problem is that by specifying multiple dtypes, you are essentially making a 1D-array of tuples (actually `np.void`), which cannot be described by stats as it includes multiple different types, incl. strings.

## Method 1

```import pandas as pd
import numpy as np

df_describe = pd.DataFrame(dataset)
df_describe.describe()
```

```import pandas as pd
import numpy as np

df_describe.describe()```

## Method 2

This is not a pretty solution, but it gets the job done. The problem is that by specifying multiple dtypes, you are essentially making a 1D-array of tuples (actually `np.void`), which cannot be described by stats as it includes multiple different types, incl. strings.

This could be resolved by either reading it in two rounds, or using pandas with `read_csv`.

If you decide to stick to `numpy`:

```import numpy as np
a = np.genfromtxt('sample.txt', delimiter=",",unpack=True,usecols=range(1,9))
s = np.genfromtxt('sample.txt', delimiter=",",unpack=True,usecols=0,dtype='|S1')

from scipy import stats
for arr in a: #do not need the loop at this point, but looks prettier
print(stats.describe(arr))
#Output per print:
DescribeResult(nobs=6, minmax=(0.34999999999999998, 0.70999999999999996), mean=0.54500000000000004, variance=0.016599999999999997, skewness=-0.3049304880932534, kurtosis=-0.9943046886340534)
```

Note that in this example the final array has `dtype` as `float`, not `int`, but can easily (if necessary) be converted to int using `arr.astype(int)`

## Summery

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.