Series methods
_obj = pandas_obj
instance-attribute
__init__(pandas_obj)
assert_data(condition, pass_message=' ✔️ Assertion passed ', fail_message=' ㄨ Assertion failed ', raise_exception=True, exception_to_raise=DataError, message_shows_condition=True, verbose=False)
Tests whether Series meets condition. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
condition |
Callable
|
Assertion criteria in the form of a lambda function, such as |
required |
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assertion passed '
|
fail_message |
str
|
Message to display if the condition fails. |
' ㄨ Assertion failed '
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
DataError
|
message_shows_condition |
bool
|
Whether the fail/pass message should also print the assertion criteria |
True
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_datetime(pass_message=' ✔️ Assert datetime passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series is datetime or timestamp. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert datetime passed '
|
fail_message |
Union[str, None]
|
Message to display if the condition fails. |
None
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
TypeError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_float(pass_message=' ✔️ Assert float passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series is floats. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert float passed '
|
fail_message |
Union[str, None]
|
Message to display if the condition fails. |
None
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
TypeError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_greater_than(min, or_equal_to=True, pass_message=' ✔️ Assert minimum passed ', fail_message=' ㄨ Assert minimum failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series is > or >= a value. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
min |
Any
|
the minimum value to compare Series to. Accepts any type that can be used in >, such as int, float, str, datetime |
required |
or_equal_to |
bool
|
whether to test for >= min (True) or > min (False) |
True
|
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert minimum passed '
|
fail_message |
str
|
Message to display if the condition fails. |
' ㄨ Assert minimum failed '
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
DataError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_int(pass_message=' ✔️ Assert integeer passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series is integers. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_less_than(max, or_equal_to=True, pass_message=' ✔️ Assert maximum passed ', fail_message=' ㄨ Assert maximum failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series is < or <= a value. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
max |
Any
|
the max value to compare Series to. Accepts any type that can be used in <, such as int, float, str, datetime |
required |
or_equal_to |
bool
|
whether to test for <= min (True) or < max (False) |
True
|
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert maximum passed '
|
fail_message |
str
|
Message to display if the condition fails. |
' ㄨ Assert maximum failed '
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
DataError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_negative(assert_not_null=True, pass_message=' ✔️ Assert negative passed ', fail_message=' ㄨ Assert negative failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series has all negative values. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
assert_not_null |
bool
|
Whether to also enforce that data has no nulls. |
True
|
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert negative passed '
|
fail_message |
str
|
Message to display if the condition fails. |
' ㄨ Assert negative failed '
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
DataError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_not_null(pass_message=' ✔️ Assert no nulls passed ', fail_message=' ㄨ Assert no nulls failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series has no nulls. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_null(pass_message=' ✔️ Assert all nulls passed ', fail_message=' ㄨ Assert all nulls failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series has all nulls. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_positive(assert_not_null=True, pass_message=' ✔️ Assert positive passed ', fail_message=' ㄨ Assert positive failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series has all positive values. Optionally raises an exception. Does not modify the Series itself.
Args:
assert_not_null: Whether to also enforce that data has no nulls.
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_str(pass_message=' ✔️ Assert string passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series is strings. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_timedelta(pass_message=' ✔️ Assert timedelta passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series is of type timedelta. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_type(dtype, pass_message=' ✔️ Assert type passed ', fail_message=None, raise_exception=True, exception_to_raise=TypeError, verbose=False)
Tests whether Series meets type assumption. Optionally raises an exception. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
dtype |
Type[Any]
|
The required variable type |
required |
pass_message |
str
|
Message to display if the condition passes. |
' ✔️ Assert type passed '
|
fail_message |
Union[str, None]
|
Message to display if the condition fails. |
None
|
raise_exception |
bool
|
Whether to raise an exception if the condition fails. |
True
|
exception_to_raise |
Type[BaseException]
|
The exception to raise if the condition fails and raise_exception is True. |
TypeError
|
verbose |
bool
|
Whether to display the pass message if the condition passes. |
False
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
assert_unique(pass_message=' ✔️ Assert unique passed ', fail_message=' ㄨ Assert unique failed ', raise_exception=True, exception_to_raise=DataError, verbose=False)
Tests whether Series has no duplicate rows. Optionally raises an exception. Does not modify the Series itself.
Args:
pass_message: Message to display if the condition passes.
fail_message: Message to display if the condition fails.
raise_exception: Whether to raise an exception if the condition fails.
exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
verbose: Whether to display the pass message if the condition passes.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
describe(fn=lambda s: s, check_name='📏 Distribution', **kwargs)
Displays descriptive statistics about a Series, without modifying the Series itself.
See Pandas docs for describe() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas describe(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check to preface the result with. |
'📏 Distribution'
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas describe() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
disable_checks(enable_asserts=True)
Turns off Pandas Checks globally, such as in production mode. Calls to .check functions will not be run. Does not modify the Series itself.
Args enable_assert: Optionally, whether to also enable or disable assert statements
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
dtype(fn=lambda s: s, check_name='🗂️ Data type')
Displays the data type of a Series, without modifying the Series itself.
See Pandas docs for .dtype for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas dtype. Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check to preface the result with. |
'🗂️ Data type'
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
enable_checks(enable_asserts=True)
Globally enables Pandas Checks. Subequent calls to .check methods will be run. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
enable_asserts |
bool
|
Optionally, whether to globally enable or disable calls to .check.assert_data(). |
True
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
function(fn=lambda s: s, check_name=None)
Applies an arbitrary function on a Series and shows the result, without modifying the Series itself.
Example
.check.function(fn=lambda s: s.shape[0]>10, check_name='Has at least 10 rows?') which will result in 'True' or 'False'
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
The lambda function to apply to the Series. Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check to preface the result with. |
None
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
get_mode(check_name='⚙️ Pandas Checks mode')
Displays the current values of Pandas Checks global options enable_checks and enable_asserts. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
check_name |
Union[str, None]
|
An optional name for the check. Will be used as a preface the printed result. |
'⚙️ Pandas Checks mode'
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
head(n=5, fn=lambda s: s, check_name=None)
Displays the first n rows of a Series, without modifying the Series itself.
See Pandas docs for head() for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
n |
int
|
The number of rows to display. |
5
|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas head(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
hist(fn=lambda s: s, check_name=None, **kwargs)
Displays a histogram for the Series's distribution, without modifying the Series itself.
See Pandas docs for hist() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas head(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas hist() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
Note
Plots are only displayed when code is run in IPython/Jupyter, not in terminal.
info(fn=lambda s: s, check_name='ℹ️ Series info', **kwargs)
Displays summary information about a Series, without modifying the Series itself.
See Pandas docs for info() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas info(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
'ℹ️ Series info'
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas info() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
memory_usage(fn=lambda s: s, check_name='💾 Memory usage', **kwargs)
Displays the memory footprint of a Series, without modifying the Series itself.
See Pandas docs for memory_usage() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas memory_usage(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
'💾 Memory usage'
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas memory_usage() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
Note
Include argument deep=True
to get further memory usage of object dtypes. See Pandas docs for memory_usage() for more info.
ndups(fn=lambda s: s, check_name=None, **kwargs)
Displays the number of duplicated rows in the Series, without modifying the Series itself.
See Pandas docs for duplicated() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before counting the number of duplicates. Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas duplicated() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
nnulls(fn=lambda s: s, check_name='👻 Rows with NaNs')
Displays the number of rows with null values in the Series, without modifying the Series itself.
See Pandas docs for isna() for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before counting rows with nulls. Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
'👻 Rows with NaNs'
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
nrows(fn=lambda s: s, check_name='☰ Rows')
Displays the number of rows in a Series, without modifying the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before counting the number of rows. Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
'☰ Rows'
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
nunique(fn=lambda s: s, check_name=None, **kwargs)
Displays the number of unique rows in a Series, without modifying the Series itself.
See Pandas docs for nunique() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas nunique(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas nunique() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
plot(fn=lambda s: s, check_name='', **kwargs)
Displays a plot of the Series, without modifying the Series itself.
See Pandas docs for plot() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas plot(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional title for the plot. |
''
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas plot() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
Note
Plots are only displayed when code is run in IPython/Jupyter, not in terminal.
If you pass a 'title' kwarg, it becomes the plot title, overriding check_name
print(object=None, fn=lambda s: s, check_name=None, max_rows=10)
Displays text, another object, or (by default) the current DataFrame's head. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
object |
Any
|
Object to print. Can be anything printable: str, int, list, another DataFrame, etc. If None, print the Series's head (with |
None
|
fn |
Callable
|
An optional lambda function to apply to the Series before printing |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
max_rows |
int
|
Maximum number of rows to print if object=None. |
10
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
print_time_elapsed(start_time, lead_in='Time elapsed', units='auto')
Displays the time elapsed since start_time.
Args: start_time: The index time when the stopwatch started, which comes from the Pandas Checks start_timer() lead_in: Optional text to print before the elapsed time. units: The units in which to display the elapsed time. Allowed values: "auto", "milliseconds", "seconds", "minutes", "hours" or shorthands "ms", "s", "m", "h".
Raises:
Type | Description |
---|---|
ValueError
|
If |
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
reset_format()
Globally restores all Pandas Checks formatting options to their default "factory" settings. Does not modify the Series itself.
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
set_format(**kwargs)
Configures selected formatting options for Pandas Checks. Run pandas_checks.describe_options() to see a list of available options. Does not modify the Series itself
For example, .check.set_format(check_text_tag= "h1", use_emojis=False`) will globally change Pandas Checks to display text results as H1 headings and remove all emojis.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
**kwargs |
Any
|
Pairs of setting name and its new value. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
set_mode(enable_checks, enable_asserts)
Configures the operation mode for Pandas Checks globally. Does not modify the Series itself.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
enable_checks |
bool
|
Whether to run any Pandas Checks methods globally. Does not affect .check.assert_data(). |
required |
enable_asserts |
bool
|
Whether to run calls to Pandas Checks .check.assert_data() globally. |
required |
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
shape(fn=lambda s: s, check_name='📐 Shape')
Displays the Series's dimensions, without modifying the Series itself.
See Pandas docs for shape
for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
'📐 Shape'
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
Note
See also .check.nrows()
tail(n=5, fn=lambda s: s, check_name=None)
Displays the last n rows of the Series, without modifying the Series itself.
See Pandas docs for tail() for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
n |
int
|
Number of rows to show. |
5
|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas tail(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
unique(fn=lambda s: s, check_name=None)
Displays the unique values in a Series, without modifying the Series itself.
See Pandas docs for unique() for additional usage information.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas unique(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
value_counts(fn=lambda s: s, max_rows=10, check_name=None, **kwargs)
Displays the value counts for a Series, without modifying the Series itself.
See Pandas docs for value_counts() for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
max_rows |
int
|
Maximum number of rows to show in the value counts. |
10
|
fn |
Callable
|
An optional lambda function to apply to the Series before running Pandas value_counts(). Example: |
lambda s: s
|
check_name |
Union[str, None]
|
An optional name for the check, to be printed as preface to the result. |
None
|
**kwargs |
Any
|
Optional, additional arguments that are accepted by Pandas value_counts() method. |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
write(path, format=None, fn=lambda s: s, verbose=False, **kwargs)
Exports Series to file, without modifying the Series itself.
Format is inferred from path extension like .csv.
This functions uses the corresponding Pandas export function such as to_csv(). See Pandas docs for those functions for additional usage information, including more configuration options you can pass to this Pandas Checks method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
path |
str
|
Path to write the file to. |
required |
format |
Union[str, None]
|
Optional file format to force for the export. If None, format is inferred from the file's extension in |
None
|
fn |
Callable
|
An optional lambda function to apply to the Series before exporting. Example: |
lambda s: s
|
verbose |
bool
|
Whether to print a message when the file is written. |
False
|
**kwargs |
Any
|
Optional, additional keyword arguments to pass to the Pandas export function (.to_csv). |
{}
|
Returns:
Type | Description |
---|---|
Series
|
The original Series, unchanged. |
Note
Exporting to some formats such as Excel, Feather, and Parquet may require you to install additional packages.