# dask.dataframe.Series.str.isnumeric

#### dataframe.Series.str.isnumeric()

Check whether all characters in each string are numeric.

This docstring was copied from pandas.core.strings.accessor.StringMethods.isnumeric.

Some inconsistencies with the Dask version may exist.

This is equivalent to running the Python string method
[`str.isnumeric()`](https://docs.python.org/3/builtins/stdtypes.html#str.isnumeric) for each element of the Series/Index. If a string
has zero characters, `False` is returned for that check.

* **Returns:**
  Series or Index of bool
  : Series or Index of boolean values with the same length as the original
    Series/Index.

#### SEE ALSO
`Series.str.isalpha`
: Check whether all characters are alphabetic.

`Series.str.isalnum`
: Check whether all characters are alphanumeric.

`Series.str.isdigit`
: Check whether all characters are digits.

`Series.str.isdecimal`
: Check whether all characters are decimal.

`Series.str.isspace`
: Check whether all characters are whitespace.

`Series.str.islower`
: Check whether all characters are lowercase.

`Series.str.isascii`
: Check whether all characters are ascii.

`Series.str.isupper`
: Check whether all characters are uppercase.

`Series.str.istitle`
: Check whether all characters are titlecase.

### Examples

The `s.str.isnumeric` method is the same as `s3.str.isdigit` but
also includes other characters that can represent quantities such as
unicode fractions.

```pycon
>>> s1 = pd.Series(["one", "one1", "1", "", "³", "⅕"])
>>> s1.str.isnumeric()
0    False
1    False
2     True
3    False
4     True
5     True
dtype: bool
```

For a string to be considered numeric, all its characters must have a Unicode
numeric property matching `str.is_numeric()`. As a consequence,
the following cases are **not** recognized as numeric:

- **Decimal numbers** (e.g., “1.1”): due to period `"."`
- **Negative numbers** (e.g., “-5”):  due to minus sign `"-"`
- **Scientific notation** (e.g., “1e3”): due to characters like `"e"`

```pycon
>>> s2 = pd.Series(["1.1", "-5", "1e3"])
>>> s2.str.isnumeric()
0    False
1    False
2    False
dtype: bool
```

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