swat.cas.table.CASColumn

class swat.cas.table.CASColumn(name, **table_params)

Bases: swat.cas.table.CASTable

Special subclass of CASTable for holding single columns

__init__(self, name, **table_params)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(self, name, \*\*table_params)	Initialize self.
abs(self)	Return absolute values element-wise
add(self, other[, level, fill_value, axis])	Addition of CASColumn with other, element-wise
all(self[, axis, bool_only, skipna, level])	Return whether all elements are True
any(self[, axis, bool_only, skipna, level])	Return True for each column with one or more element treated as true
append(self, other[, ignore_index, …])	Append rows of other to self
append_columns(self, \*items, \*\*kwargs)	Append variable names to action inputs parameter
append_computed_columns(self, names, code[, …])	Append computed columns as specified
append_computedvars(self, \*items, \*\*kwargs)	Append variable names to computedvars parameter
append_computedvarsprogram(self, \*items, …)	Append code to computedvarsprogram parameter
append_groupby(self, \*items, \*\*kwargs)	Append variable names to groupby parameter
append_orderby(self, \*items, \*\*kwargs)	Append orderby parameters
append_where(self, \*items, \*\*kwargs)	Append code to where parameter
as_matrix(self[, columns, n])	Represent CASTable as a Numpy array
between(self, left, right[, inclusive])	Return boolean CASColumn equivalent to left <= value <= right
boxplot(self[, column, by])	Make a boxplot from the table data
clip(self[, lower, upper, out, axis])	Trim values at input threshold(s)
clip_lower(self, threshold[, axis])	Trim values below given threshold
clip_upper(self, threshold[, axis])	Trim values above given threshold
copy(self[, deep, exclude])	Make a copy of the CASTable object
corr(self, other[, method, min_periods])	Compute correlation with other column
count(self[, level])	Return the number of non-NA/null observations in the CASColumn
css(self[, casout])	Return corrected sum of squares of the values
cv(self[, casout])	Return coefficient of variation of the values
datastep(self, code[, casout])	Execute Data step code against the table
del_action_params(self, \*names)	Delete parameters for specified action names
del_param(self, \*keys)	Delete parameters
del_params(self, \*keys)	Delete parameters
describe(self[, percentiles, include, …])	Generate various summary statistics
div(self, other[, level, fill_value, axis])	Floating division of CASColumn and other, element-wise
drop(self, labels[, axis, level, inplace, …])	Return a new CASTable object with the specified columns removed
drop_duplicates(self, casout[, subset])	Remove duplicate rows from a CASTable.
dropna(self[, axis, how, thresh, subset, …])	Drop rows that contain missing values
eq(self, other[, axis])	Equal-to comparison of CASColumn and other, element-wise
eval(self, expr[, inplace, kwargs])	Evaluate a CAS table expression
exists(self)	Return True if table exists in the server
fillna(self[, value, method, axis, inplace, …])	Fill missing values using the specified method
floordiv(self, other[, level, fill_value, axis])	Integer division of CASColumn and other, element-wise
from_csv(connection, path[, header, sep, …])	Create a CASColumn from a CSV file
from_dict(connection, data[, casout])	Create a CASTable from a dictionary
from_items(connection, items[, casout])	Create a CASTable from a (key, value) pairs
from_records(connection, data[, casout])	Create a CASTable from records
ge(self, other[, axis])	Greater-than-or-equal-to comparison of CASColumn and other, element-wise
get(self, key[, default])	Get item from CASColumn for the given key
get_action_names(self)	Return a list of available CAS actions
get_action_params(self, name, \*default)	Return parameters for specified action name
get_actionset_names(self)	Return a list of available actionsets
get_connection(self)	Get the registered connection object
get_dtype_counts(self)	Retrieve the frequency of CAS table column data types
get_fetch_params(self)	Return options to be used during the table.fetch action
get_ftype_counts(self)	Retrieve the frequency of CAS table column data types
get_groupby_vars(self)	Return a list of By group variable names
get_inputs_param(self)	Return the column names for the inputs= action parameter
get_param(self, key, \*default)	Return the value of a parameter
get_params(self, \*keys)	Return the values of one or more parameters
get_value(self, index, col, \*\*kwargs)	Retrieve a single scalar value
groupby(self, by[, axis, level, as_index, …])	Specify grouping variables for the table
gt(self, other[, axis])	Greater-than comparison of CASColumn and other, element-wise
has_groupby_vars(self)	Return True if the table has By group variables configured
has_param(self, \*keys)	Return True if the specified parameters exist
has_params(self, \*keys)	Return True if the specified parameters exist
head(self[, n, bygroup_as_index, casout])	Return first n rows of the column in a Series
hist(self[, column, by])	Make a histogram from the table data
info(self[, verbose, buf, max_cols, …])	Print summary of CASTable information
invoke(self, _name_, \*\*kwargs)	Invoke an action on the registered connection
isin(self, values)	Return a boolean CASColumn indicating if the value is in the given values
isnull(self)	Return a boolean CASColumn indicating if the values are null
iteritems(self[, chunksize])	Lazily iterate over (index, value) tuples
iterrows(self[, chunksize])	Iterate over the rows of a CAS table as (index, pandas.Series) pairs
itertuples(self[, index, chunksize])	Iterate over rows as tuples
kurt(self[, casout])	Return kurtosis
kurtosis(self[, casout])	Return kurtosis
le(self, other[, axis])	Less-than-or-equal-to comparison of CASColumn and other, element-wise
lookup(self, row_labels, col_labels)	Retrieve values indicated by row_labels, col_labels positions
lt(self, other[, axis])	Less-than comparison of CASColumn and other, element-wise
max(self[, axis, skipna, level, casout])	Return the maximum value
mean(self[, axis, skipna, level, casout])	Return the mean value
median(self[, q, axis, interpolation, casout])	Return the median value
merge(self, right[, how, on, left_on, …])	Merge CASTable objects using a database-style join on a column
min(self[, axis, skipna, level, casout])	Return the minimum value
mod(self, other[, level, fill_value, axis])	Modulo of CASColumn and other, element-wise
mode(self[, axis, max_tie])	Return the mode values
mul(self, other[, level, fill_value, axis])	Multiplication of CASColumn with other, element-wise
ne(self, other[, axis])	Not-equal-to comparison of CASColumn and other, element-wise
next(self)	Return next item in the iteration
nlargest(self[, n, keep, casout])	Return the n largest values
nmiss(self[, casout])	Return number of missing values
notnull(self)	Return a boolean CASColumn indicating if the values are not null
nsmallest(self[, n, keep, casout])	Return the n smallest values
nth(self, n[, dropna, bygroup_as_index, casout])	Return the `n`th row
nunique(self[, dropna, casout])	Return number of unique elements in the CASColumn
pop(self, colname)	Remove a column from the CASTable and return it
pow(self, other[, level, fill_value, axis])	Exponential power of CASColumn and other, element-wise
probt(self[, casout])	Return p-value of the T-statistic
quantile(self[, q, axis, interpolation, casout])	Return the value at the given quantile
query(self, expr[, inplace, engine])	Query the table with a boolean expression
radd(self, other[, level, fill_value, axis])	Addition of CASColumn and other, element-wise
rdiv(self, other[, level, fill_value, axis])	Floating division of CASColumn and other, element-wise
rename(self, columns[, errors])	Rename columns of the CASTable.
replace(self[, to_replace, value, inplace, …])	Replace values in the data set
reset_index(self[, level, drop, inplace, …])	Reset the CASTable index
retrieve(self, _name_, \*\*kwargs)	Invoke an action on the registered connection and retrieve results
rfloordiv(self, other[, level, fill_value, axis])	Integer division of CASColumn and other, element-wise
rmod(self, other[, level, fill_value, axis])	Modulo of CASColumn and other, element-wise
rmul(self, other[, level, fill_value, axis])	Multiplication of CASColumn and other, element-wise
round(self[, decimals, out])	Round each value of the CASColumn to the given number of decimals
rpow(self, other[, level, fill_value, axis])	Exponential power of CASColumn and other, element-wise
rsub(self, other[, level, fill_value, axis])	Subtraction of CASColumn and other, element-wise
rtruediv(self, other[, level, fill_value, axis])	Floating division of CASColumn and other, element-wise
sample(self[, n, frac, replace, weights, …])	Returns a random sample of the table rows
select_dtypes(self[, include, exclude, inplace])	Return a subset CASTable including/excluding columns based on data type
set_action_params(self, name, \*\*kwargs)	Set parameters for specified action name
set_connection(self, connection)	Set the connection to use for action calls
set_param(self, \*args, \*\*kwargs)	Set paramaters according to key-value pairs
set_params(self, \*args, \*\*kwargs)	Set paramaters according to key-value pairs
skew(self[, casout])	Return skewness
skewness(self[, casout])	Return skewness
slice(self[, start, stop, bygroup_as_index, …])	Return from rows from start to stop in a Series
sort(self[, axis, ascending, inplace, kind, …])	Apply sort order parameters to fetches of the data in this column
sort_values(self[, axis, ascending, …])	Apply sort order parameters to fetches of the data in this column
std(self[, axis, skipna, level, ddof, casout])	Return the standard deviation of the values
stderr(self[, casout])	Return standard error of the values
sub(self, other[, level, fill_value, axis])	Subtraction of CASColumn with other, element-wise
sum(self[, axis, skipna, level, casout])	Return the sum of the values
tail(self[, n, bygroup_as_index, casout])	Return last n rows of the column in a Series
to_clipboard(self, \*args, \*\*kwargs)	Write the table data to the clipboard
to_csv(self, \*args, \*\*kwargs)	Write table data to comma-separated values (CSV)
to_datastep_params(self)	Create a data step table specification
to_dense(self, \*args, \*\*kwargs)	Return dense representation of table data
to_dict(self, \*args, \*\*kwargs)	Convert table data to a Python dictionary
to_excel(self, \*args, \*\*kwargs)	Write table data to an Excel spreadsheet
to_frame(self, \*args, \*\*kwargs)	Convert CASColumn to a pandas.DataFrame
to_gbq(self, \*args, \*\*kwargs)	Write table data to a Google BigQuery table
to_hdf(self, \*args, \*\*kwargs)	Write table data to HDF
to_html(self, \*args, \*\*kwargs)	Render the table data to an HTML table
to_input_datastep_params(self)	Create an input data step table specification
to_json(self, \*args, \*\*kwargs)	Convert the table data to a JSON string
to_latex(self, \*args, \*\*kwargs)	Render the table data to a LaTeX tabular environment
to_msgpack(self, \*args, \*\*kwargs)	Write table data to msgpack object
to_outtable(self)	Create a copy of the CASTable object with only output table paramaters
to_outtable_params(self)	Create a copy of the CASTable parameters using only the output table parameters
to_params(self)	Return parameters of CASTable object
to_pickle(self, \*args, \*\*kwargs)	Pickle (serialize) the table data
to_records(self, \*args, \*\*kwargs)	Convert table data to record array
to_series(self, \*args, \*\*kwargs)	Retrieve all elements into a Series
to_sparse(self, \*args, \*\*kwargs)	Convert table data to SparseDataFrame
to_sql(self, \*args, \*\*kwargs)	Write table records to SQL database
to_stata(self, \*args, \*\*kwargs)	Write table data to Stata file
to_string(self, \*args, \*\*kwargs)	Render the table to a console-friendly tabular output
to_table(self)	Create a copy of the CASTable object with only input table paramaters
to_table_name(self)	Return the name of the table
to_table_params(self)	Create a copy of the table parameters containing only input table parameters
to_view(self, \*args, \*\*kwargs)	Create a view using the current CASTable parameters
to_xarray(self, \*args, \*\*kwargs)	Return an xarray object from the CASColumn
tolist(self)	Return a list of the column values
truediv(self, other[, level, fill_value, axis])	Floating division of CASColumn and other, element-wise
tvalue(self[, casout])	Return value of T-statistic for hypothetical testing
unique(self[, casout])	Return array of unique values in the CASColumn
uss(self[, casout])	Return uncorrected sum of squares of the values
value_counts(self[, normalize, sort, …])	Return object containing counts of unique values
var(self[, axis, skipna, level, ddof, casout])	Return the unbiased variance of the values
with_params(self, \*\*kwargs)	Create copy of table with kwargs inserted as parameters
xs(self, \*args, \*\*kwargs)	Only exists for CASTable

Attributes

all_params
at
axes	Return the row axis labels and column axis labels
columns	The visible columns in the table
created_date	Return the created date of the table in the server
dt	Accessor for the datetime methods
dtype	The data type of the underlying data
dtypes	Series of the data types in the table
ftype	The data type and whether it is sparse or dense
ftypes	Series of the ftypes (indication of sparse/dense and dtype) in the table
getdoc
iat
iloc	Integer-based indexer for selecting by position
index	The table index
is_unique	Return boolean indicating if the values in the CASColumn are unique
itemsize	Return the size of the data type of the underlying data
ix	Label-based indexer with integer position fallback
last_accessed_date	Return the last access date of the table in the server
last_modified_date	Return the last modified date of the table in the server
loc	Label-based indexer
name	Return the column name
ndim	Return the number of dimensions of the underlying data
outtable_params
param_names
plot	Plot the data in the table
sas	Accessor for the sas methods
shape	Return a tuple of the shape of the underlying data
size	Return the number of elements in the underlying data
str	Accessor for string methods
table_params
values	Return column data as numpy.ndarray()