tally.dataset.DataSet

class tally.dataset.DataSet(api_key=None, host='tally.datasmoothie.com', ssl=True, use_futures=False)

A class that wraps a dataset and has all the information needed to send to the API in order to perform the various tasks.

Parameters

name (string) – Name for the dataset

__init__(api_key=None, host='tally.datasmoothie.com', ssl=True, use_futures=False)

Methods

__init__([api_key, host, ssl, use_futures])
add_column_to_data(name, data, new_meta)
add_credentials([api_key, host, ssl])	Add your API key and what server it is authorized to connect to.
band(**kwargs)	Group numeric data with band definitions treated as group text labels.
build_excel([data_params, filename])
build_excel_from_dataframes([data_params, ...])
build_powerpoint([data_params, filename, ...])
compare(**kwargs)	Compares types, codes, values, question labels of two datasets.
convert_data_to_csv_json(**kwargs)	Converts data, either sent or from an external source to Quantipy CSV and JSON.
convert_data_to_sav(**kwargs)	Converts data, either sent or from an external source to an SPSS sav file.
convert_spss_to_csv_json([data_params])
copy(**kwargs)	Copy meta and case data of the variable defintion given per name.
crosstab([data_params])
derive(**kwargs)	Create meta and recode case data by specifying derived category logics.
extend_values(**kwargs)	Add an answer/value and code to the list of answer/values/codes already in the meta data for the variable.
feature_select(**kwargs)	Shows the variables that score the highest with a given ML features select algorithm
filter(**kwargs)	Filter the DataSet using a logical expression.
find(**kwargs)	Find variables by searching their names for substrings.
get_dataframe()
get_variable_text(**kwargs)	Return the variables text label information.
hmerge(**kwargs)	Merge Quantipy datasets together by appending rows.
joined_crosstab(**kwargs)	Does crosstab tabulation using the provided parameters, allowing for multiple datasources to be sent along with the request to run multiple crosstabs in one result.
merge_column_to_data(name, data, new_meta, ...)
meta(**kwargs)	Shows the meta-data for a variable
prepare_post_params(data_params[, params])
recode(**kwargs)	Create a new or copied series from data, recoded using a mapper.
remove_values(**kwargs)	Erase value codes safely from both meta and case data components.
set_value_texts(**kwargs)	Rename or add value texts in the ‘values’ object.
set_variable_text(**kwargs)	Change the variable text for a named variable.
sum(**kwargs)	Adds all values in each column and returns the sum for each column.
to_array(**kwargs)	Create a new variable grid (array) variable from two or more single variables with the same labels.
to_delimited_set(**kwargs)	Create a new variable delimited set (multi choice) variable from two or more single variables.
use_confirmit(source_projectid, ...)	Load remote Forsta/Confirmit data into the dataset as the data to send with all requests.
use_csv(csv_file)	Load CSV file into the dataset as the file to send with all requests.
use_nebu(nebu_url)	Load remote Nebu/Enghouse file into the dataset as the file to send with all requests.
use_parquet(pq_data_filename[, pq_meta_filename])	Load parquet file into memory as the file to send with all requests.
use_quantipy(meta_json, data_csv)	Load Quantipy meta and data files to this dataset.
use_spss(file_path)	Load SPSS file into memory as the file to send with all requests.
use_unicom(mdd_filename, ddf_filename)	Load parquet file into memory as the file to send with all requests.
values(**kwargs)	Get a list of value texts and codes for a categorical variable, as a dictionary.
variables(**kwargs)	Shows list of variables.
vmerge(**kwargs)	Merge Quantipy datasets together by appending rows.
weight([data_params])
write_quantipy(file_path_json, file_path_csv)	Write the case and meta data as Quantipy compatible json and csv files.
write_spss(file_path, data_params, **kwargs)	Writes the dataset to an SPSS (sav) file.

Attributes

dataset_type
qp_data
qp_meta
sav_data
tally