Module ImportFrom alias ImportFrom alias Import alias identifier ImportFrom alias Import alias identifier ImportFrom alias FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults Num body Expr Str Assign NameStore Lambda arguments args NameParam defaults Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore BinOpMult BinOpMult BinOpDiv Num NameLoad BinOpPow BinOpDiv BinOpAdd BinOpMult NameLoad NameLoad Num BinOpSub NameLoad Num Num BinOpPow BinOpAdd Call NameLoad BinOpSub Num BinOpDiv NameLoad Num Call NameLoad NameLoad Num Assign NameStore BinOpDiv BinOpMult NameLoad NameLoad BinOpAdd BinOpMult NameLoad NameLoad NameLoad Assign NameStore BinOpDiv NameLoad BinOpAdd BinOpMult NameLoad NameLoad NameLoad Return TupleLoad Call NameLoad Call AttributeLoad NameLoad attr NameLoad Call NameLoad Call AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults Num body Expr Str Assign NameStore Lambda arguments args NameParam defaults Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Assign NameStore BinOpAdd BinOpMult NameLoad NameLoad BinOpMult NameLoad NameLoad Assign NameStore BinOpDiv Call NameLoad NameLoad Call NameLoad NameLoad Return Call AttributeLoad AttributeLoad NameLoad attr attr BinOpSub BinOpDiv BinOpMult Call AttributeLoad NameLoad attr BinOpMult NameLoad NameLoad Call NameLoad BinOpSub NameLoad Num BinOpAdd BinOpMult NameLoad NameLoad Num Call NameLoad BinOpSub Num BinOpDiv NameLoad Num decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad Num Num kwarg body Expr Str Assign TupleStore NameStore NameStore TupleLoad Call AttributeLoad NameLoad attr NameLoad Call AttributeLoad NameLoad attr NameLoad If CompareIs NameLoad NameLoad body Assign NameStore Call AttributeLoad NameLoad attr SubscriptLoad AttributeLoad NameLoad attr Index Num If CompareIs NameLoad NameLoad body Assign NameStore Call AttributeLoad NameLoad attr SubscriptLoad AttributeLoad NameLoad attr Index Num Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index TupleLoad NameLoad NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index TupleLoad Call AttributeLoad NameLoad attr SubscriptLoad AttributeLoad NameLoad attr Index Num keyword NameLoad Call AttributeLoad NameLoad attr SubscriptLoad AttributeLoad NameLoad attr Index Num keyword NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index TupleLoad NameLoad NameLoad Return Call NameLoad NameLoad NameLoad NameLoad keyword NameLoad keyword NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad Num Num NameLoad kwarg body Expr Str If CompareIs NameLoad NameLoad body Assign NameStore Call AttributeLoad NameLoad attr TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Num Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Assert CompareEqEq NameLoad Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Str Assign TupleStore NameStore NameStore NameStore Call NameLoad Lambda arguments args NameParam defaults Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr NameLoad TupleLoad NameLoad ListLoad NameLoad NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index Num If NameLoad body Assign NameStore BinOpMult BinOpMult Num NameLoad BinOpSub NameLoad Num Assign NameStore BinOpSub Num BinOpDiv BinOpSub Num NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr TupleLoad NameLoad NameLoad keyword NameLoad Expr Call AttributeLoad NameLoad attr NameLoad NameLoad For TupleStore NameStore NameStore Call NameLoad Call AttributeLoad NameLoad attr NameLoad Num body Assign TupleStore NameStore NameStore SubscriptLoad NameLoad Index ListLoad NameLoad NameLoad Assign TupleStore NameStore NameStore TupleLoad CompareEq NameLoad NameLoad CompareEq NameLoad NameLoad Assign NameStore BinOpAdd BinOpAdd Call NameLoad NameLoad Str Call NameLoad NameLoad Assign NameStore Call NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad SubscriptLoad AttributeLoad NameLoad attr Index NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad NameLoad Assign TupleStore SubscriptStore NameLoad Index TupleLoad NameLoad NameLoad SubscriptStore NameLoad Index TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad Return Call AttributeLoad NameLoad attr NameLoad keyword NameLoad keyword NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam defaults NameLoad Num Num kwarg body Expr Str If UnaryOpNot CompareLtLtE Num NameLoad Num body Raise Call NameLoad Str Assign TupleStore NameStore NameStore TupleLoad Call AttributeLoad NameLoad attr NameLoad Call AttributeLoad NameLoad attr NameLoad If CompareIs NameLoad NameLoad body Assign NameStore Call AttributeLoad NameLoad attr TupleLoad SubscriptLoad AttributeLoad NameLoad attr Index Num Num orelse Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Assert CompareEqEq NameLoad Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Str Assign TupleStore NameStore NameStore NameStore Call NameLoad Lambda arguments args NameParam defaults Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr NameLoad TupleLoad NameLoad ListLoad NameLoad NameLoad NameLoad Assign TupleStore NameStore NameStore NameStore NameStore Call NameLoad NameLoad NameLoad NameLoad keyword NameLoad Assign NameStore SubscriptLoad AttributeLoad NameLoad attr Index Num Assign NameStore AttributeLoad Call AttributeLoad NameLoad attr Num attr Assign NameStore BinOpSub AttributeLoad Call AttributeLoad NameLoad attr Num attr Call AttributeLoad Call AttributeLoad Call AttributeLoad NameLoad attr Num attr Num attr Num Assign NameStore Call AttributeLoad NameLoad attr Num Assign NameStore BinOpSub Call AttributeLoad AttributeLoad NameLoad attr attr Call AttributeLoad Call AttributeLoad Call AttributeLoad Call AttributeLoad NameLoad attr Num attr attr Num attr Num Assign NameStore Call AttributeLoad Call AttributeLoad NameLoad attr BinOpDiv NameLoad NameLoad keyword Str attr Num Assign NameStore BinOpSub NameLoad NameLoad Assert CompareLt Call NameLoad Call AttributeLoad NameLoad attr Num Str Assign NameStore BinOpMult Call AttributeLoad BinOpDiv BinOpSub NameLoad NameLoad BinOpSub NameLoad Num attr AttributeLoad NameLoad attr Num NameLoad Assign SubscriptStore NameLoad Index Str AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad Call AttributeLoad NameLoad attr BinOpDiv Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Str attr Num Assign NameStore UnaryOpUSub Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign SubscriptStore NameLoad Index TupleLoad NameLoad NameLoad BinOpAdd UnaryOpUSub SubscriptLoad NameLoad Index TupleLoad Num NameLoad SubscriptLoad NameLoad Index TupleLoad NameLoad NameLoad Assign NameStore SubscriptLoad NameLoad ExtSlice Slice Num Slice Num Assign NameStore Call AttributeLoad SubscriptLoad AttributeLoad NameLoad attr Slice Num attr Call AttributeLoad Call AttributeLoad AttributeLoad NameLoad attr attr SubscriptLoad NameLoad ExtSlice Slice Num Slice Num attr SubscriptLoad AttributeLoad NameLoad attr Slice Num Assign TupleStore NameStore NameStore Call NameLoad NameLoad BinOpSub NameLoad Num NameLoad Return Call NameLoad NameLoad NameLoad NameLoad keyword NameLoad keyword Str keyword NameLoad keyword Str keyword BinOpSub NameLoad Num NameLoad decorator_list ClassDef bases NameLoad body FunctionDef arguments args NameParam NameParam NameParam NameParam defaults kwarg body Assign AttributeStore NameLoad attr NameLoad Assign AttributeStore NameLoad attr NameLoad Assign AttributeStore NameLoad attr IfExp NameLoad Str Str Assign AttributeStore NameLoad attr CompareIs NameLoad NameLoad For TupleStore NameStore NameStore Call AttributeLoad NameLoad attr body Expr Call NameLoad NameLoad NameLoad NameLoad Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam defaults body Expr Call NameLoad Call AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam defaults body Assign NameStore ListLoad Str Str Str Str Return Call AttributeLoad NameLoad attr ListLoad ListLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr keyword NameLoad decorator_list NameLoad FunctionDef arguments args NameParam defaults body Return BinOpMod Str Call AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam defaults body Assign NameStore Str Assign NameStore Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr Assign NameStore Str AugAssignAdd NameStore Str AugAssignAdd NameStore BinOpAdd NameLoad Str AugAssignAdd NameStore BinOpAdd NameLoad Str AugAssignAdd NameStore Call AttributeLoad Str attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr IfExp AttributeLoad NameLoad attr Str Str Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Assign NameStore Str For TupleStore NameStore NameStore Call AttributeLoad NameLoad attr body AugAssignAdd NameStore BinOpAdd BinOpAdd BinOpAdd BinOpAdd Str Call AttributeLoad Call NameLoad NameLoad attr Str Str Str Call NameLoad NameLoad Str Return NameLoad decorator_list decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad NameLoad If CompareLt NameLoad BinOpSub Num NameLoad body Return TupleLoad NameLoad NameLoad orelse Return TupleLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Assign NameStore BinOpSub Num Call AttributeLoad NameLoad attr Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad BinOpSub Num Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad If CompareLt NameLoad BinOpSub Num BinOpDiv NameLoad Num body Return TupleLoad NameLoad NameLoad orelse Return TupleLoad NameLoad NameLoad decorator_list
N/A __future__ print_function itertools combinations N/A numpy np scipy stats N/A pandas pd lifelines.utils group_survival_table_from_events sample_size_necessary_under_cph N/A N/A power ratio_of_participants p_exp p_con postulated_hazard_ratio alpha N/A 0.05 N/A N/A 
    This computes the sample size for needed power to compare two groups under a Cox
    Proportional Hazard model.

    References:
        https://cran.r-project.org/web/packages/powerSurvEpi/powerSurvEpi.pdf

    Parameters:
        power: power to detect the magnitude of the hazard ratio as small as that specified by postulated_hazard_ratio.
        ratio_of_participants: ratio of participants in experimental group over control group.
        p_exp: probability of failure in experimental group over period of study.
        p_con: probability of failure in control group over period of study
        postulated_hazard_ratio: the postulated hazard ratio
        alpha: type I error rate

    Returns:
        n_exp, n_con: the samples sizes need for the experiment and control group, respectively, to achieve desired power
     N/A z N/A N/A N/A p N/A N/A N/A N/A stats norm ppf p N/A m N/A N/A N/A 1.0 ratio_of_participants N/A N/A N/A N/A ratio_of_participants postulated_hazard_ratio 1.0 N/A postulated_hazard_ratio 1.0 2 N/A N/A N/A z N/A 1.0 N/A alpha 2.0 N/A z power 2 N/A n_exp N/A N/A m ratio_of_participants N/A N/A ratio_of_participants p_exp p_con N/A n_con N/A m N/A N/A ratio_of_participants p_exp p_con N/A N/A N/A int N/A N/A np ceil n_exp N/A int N/A N/A np ceil n_con N/A power_under_cph N/A N/A n_exp n_con p_exp p_con postulated_hazard_ratio alpha N/A 0.05 N/A N/A 
    This computes the sample size for needed power to compare two groups under a Cox
    Proportional Hazard model.

    References:
        https://cran.r-project.org/web/packages/powerSurvEpi/powerSurvEpi.pdf

    Parameters:
        n_exp: size of the experiment group.
        n_con: size of the control group.
        p_exp: probability of failure in experimental group over period of study.
        p_con: probability of failure in control group over period of study
        postulated_hazard_ratio: the postulated hazard ratio
        alpha: type I error rate

    Returns:
        power: power to detect the magnitude of the hazard ratio as small as that specified by postulated_hazard_ratio.
     N/A z N/A N/A N/A p N/A N/A N/A N/A stats norm ppf p N/A m N/A N/A n_exp p_exp N/A n_con p_con N/A k N/A N/A float n_exp N/A float n_con N/A N/A N/A N/A stats norm cdf N/A N/A N/A N/A N/A np sqrt N/A k m N/A abs N/A postulated_hazard_ratio 1 N/A N/A k postulated_hazard_ratio 1 N/A z N/A 1 N/A alpha 2.0 N/A logrank_test N/A N/A event_times_A event_times_B event_observed_A event_observed_B alpha t_0 N/A None None 0.95 -1 kwargs N/A N/A 
    Measures and reports on whether two intensity processes are different. That is, given two
    event series, determines whether the data generating processes are statistically different.
    The test-statistic is chi-squared under the null hypothesis.

    H_0: both event series are from the same generating processes
    H_A: the event series are from different generating processes.

    See Survival and Event Analysis, page 108. This implicitly uses the log-rank weights.

    Parameters:
      event_times_foo: a (nx1) array of event durations (birth to death,...) for the population.
      censorship_bar: a (nx1) array of censorship flags, 1 if observed, 0 if not. Default assumes all observed.
      t_0: the period under observation, -1 for all time.
      alpha: the level of signifiance
      kwargs: add keywords and meta-data to the experiment summary

    Returns:
      results: a StatisticalResult object with properties 'p_value', 'summary', 'test_statistic', 'test_result'

     N/A N/A event_times_A event_times_B N/A N/A N/A np array event_times_A N/A N/A np array event_times_B N/A N/A event_observed_A None N/A N/A event_observed_A N/A N/A np ones N/A N/A event_times_A shape N/A 0 N/A N/A event_observed_B None N/A N/A event_observed_B N/A N/A np ones N/A N/A event_times_B shape N/A 0 N/A event_times N/A N/A np r_ N/A N/A event_times_A event_times_B N/A groups N/A N/A np r_ N/A N/A N/A N/A np zeros N/A N/A event_times_A shape N/A 0 dtype int N/A N/A np ones N/A N/A event_times_B shape N/A 0 dtype int N/A event_observed N/A N/A np r_ N/A N/A event_observed_A event_observed_B N/A N/A multivariate_logrank_test event_times groups event_observed alpha alpha t_0 t_0 kwargs N/A pairwise_logrank_test N/A N/A event_durations groups event_observed alpha t_0 bonferroni N/A None 0.95 -1 True kwargs N/A N/A 
    Perform the logrank test pairwise for all n>2 unique groups (use the more appropriate logrank_test for n=2).
    We have to be careful here: if there are n groups, then there are n*(n-1)/2 pairs -- so many pairs increase
    the chance that here will exist a significantly different pair purely by chance. For this reason, we use the
    Bonferroni correction (rewight the alpha value higher to accomidate the multiple tests).


    Parameters:
      event_durations: a (n,) numpy array the (partial) lifetimes of all individuals
      groups: a (n,) numpy array of unique group labels for each individual.
      event_observed: a (n,) numpy array of event_observed events: 1 if observed death, 0 if censored. Defaults
          to all observed.
      alpha: the level of signifiance desired.
      t_0: the final time to compare the series' up to. Defaults to all.
      bonferroni: If true, uses the Bonferroni correction to compare the M=n(n-1)/2 pairs, i.e alpha = alpha/M
            See (here)[http://en.wikipedia.org/wiki/Bonferroni_correction].
      kwargs: add keywords and meta-data to the experiment summary.

    Returns:
        R: a (n,n) dataframe of StatisticalResults (None on the diagonal)

     N/A N/A event_observed None N/A N/A event_observed N/A N/A np ones N/A N/A N/A event_durations shape N/A 0 1 N/A n N/A N/A np max N/A event_durations shape N/A N/A n N/A N/A np max N/A event_durations shape N/A N/A np max N/A event_observed shape inputs must be of the same length. N/A N/A groups event_durations event_observed N/A map N/A N/A N/A x N/A N/A N/A pd Series N/A N/A np reshape x N/A n N/A groups event_durations event_observed N/A unique_groups N/A N/A np unique groups N/A n N/A N/A unique_groups shape N/A 0 N/A bonferroni N/A N/A m N/A N/A 0.5 n N/A n 1 N/A alpha N/A 1 N/A N/A 1 alpha m N/A R N/A N/A np zeros N/A n n dtype object N/A N/A N/A np fill_diagonal R None N/A N/A i1 i2 N/A combinations N/A N/A np arange n 2 N/A N/A N/A g1 g2 N/A unique_groups N/A N/A i1 i2 N/A N/A ix1 ix2 N/A N/A groups g1 N/A groups g2 N/A test_name N/A N/A N/A str g1  vs.  N/A str g2 N/A result N/A logrank_test N/A N/A event_durations ix N/A ix1 N/A N/A event_durations ix N/A ix2 N/A N/A event_observed ix N/A ix1 N/A N/A event_observed ix N/A ix2 alpha alpha t_0 t_0 use_bonferroni bonferroni test_name test_name kwargs N/A N/A N/A R N/A N/A i1 i2 N/A R N/A N/A i2 i1 N/A result result N/A N/A N/A pd DataFrame R columns unique_groups index unique_groups N/A multivariate_logrank_test N/A N/A event_durations groups event_observed alpha t_0 N/A None 0.95 -1 kwargs N/A N/A 
    This test is a generalization of the logrank_test: it can deal with n>2 populations (and should
      be equal when n=2):

    H_0: all event series are from the same generating processes
    H_A: there exist atleast one group that differs from the other.

    Parameters:
      event_durations: a (n,) numpy array the (partial) lifetimes of all individuals
      groups: a (n,) numpy array of unique group labels for each individual.
      event_observed: a (n,) numpy array of event observations: 1 if observed death, 0 if censored. Defaults
          to all observed.
      alpha: the level of significance desired.
      t_0: the final time to compare the series' up to. Defaults to all.
      kwargs: add keywords and meta-data to the experiment summary.

    Returns
      results: a StatisticalResult object with properties 'p_value', 'summary', 'test_statistic', 'test_result'

     N/A N/A N/A 0 alpha 1.0 N/A N/A N/A ValueError alpha parameter must be between 0 and 1. N/A N/A event_durations groups N/A N/A N/A np asarray event_durations N/A N/A np asarray groups N/A N/A event_observed None N/A N/A event_observed N/A N/A np ones N/A N/A N/A event_durations shape N/A 0 1 N/A N/A event_observed N/A N/A np asarray event_observed N/A n N/A N/A np max N/A event_durations shape N/A N/A n N/A N/A np max N/A event_durations shape N/A N/A np max N/A event_observed shape inputs must be of the same length. N/A N/A groups event_durations event_observed N/A map N/A N/A N/A x N/A N/A N/A pd Series N/A N/A np reshape x N/A n N/A groups event_durations event_observed N/A N/A unique_groups rm obs _ N/A group_survival_table_from_events groups event_durations event_observed limit t_0 N/A n_groups N/A N/A unique_groups shape N/A 0 N/A N_j N/A N/A N/A obs sum 0 values N/A n_ij N/A N/A N/A N/A rm sum 0 values N/A N/A N/A N/A N/A N/A rm cumsum 0 shift 1 fillna 0 N/A d_i N/A N/A obs sum 1 N/A n_i N/A N/A N/A N/A rm values sum N/A N/A N/A N/A N/A N/A N/A N/A rm sum 1 cumsum shift 1 fillna 0 N/A ev N/A N/A N/A N/A n_ij mul N/A d_i n_i axis index sum 0 N/A Z_j N/A N_j ev N/A N/A N/A abs N/A N/A Z_j sum 1e-07 Sum is not zero. N/A factor N/A N/A N/A N/A N/A n_i d_i N/A n_i 1 replace N/A np inf 1 d_i N/A N/A n_ij N/A _ N/A n_i values N/A V_ N/A N/A N/A N/A n_ij mul N/A N/A N/A np sqrt factor n_i axis index fillna 1 N/A V N/A N/A N/A np dot N/A V_ T V_ N/A ix N/A N/A np arange n_groups N/A N/A V N/A N/A ix ix N/A N/A N/A V N/A N/A -1 ix N/A V N/A N/A ix ix N/A V N/A V N/A N/A -1 N/A -1 N/A U N/A N/A N/A N/A Z_j iloc N/A -1 dot N/A N/A N/A N/A N/A np linalg pinv N/A V N/A N/A -1 N/A -1 dot N/A N/A Z_j iloc N/A -1 N/A N/A test_result p_value N/A chisq_test U N/A n_groups 1 alpha N/A N/A StatisticalResult test_result p_value U t_0 t_0 test logrank alpha alpha null_distribution chi squared df N/A n_groups 1 kwargs N/A StatisticalResult N/A object N/A __init__ N/A N/A self test_result p_value test_statistic N/A kwargs N/A N/A N/A self p_value p_value N/A N/A self test_statistic test_statistic N/A N/A self test_result N/A test_result Reject Null Cannot Reject Null N/A N/A self is_significant N/A test_result True N/A N/A kw value N/A N/A kwargs items N/A N/A N/A setattr self kw value N/A N/A self _kwargs kwargs N/A print_summary N/A N/A self N/A N/A N/A N/A print N/A N/A self __unicode__ N/A summary N/A N/A self N/A N/A N/A cols N/A p-value test_statistic test_result is_significant N/A N/A N/A pd DataFrame N/A N/A N/A self p_value N/A self test_statistic N/A self test_result N/A self is_significant columns cols N/A property __repr__ N/A N/A self N/A N/A N/A N/A <lifelines.StatisticalResult: 
%s
> N/A N/A self __unicode__ N/A __unicode__ N/A N/A self N/A N/A N/A HEADER    __ p-value ___|__ test statistic __|____ test result ____|__ is significant __ N/A meta_data N/A N/A self _pretty_print_meta_data N/A self _kwargs N/A s N/A s Results
 N/A s N/A meta_data N/A s N/A HEADER N/A s N/A N/A {:>16.5f} | {:>18.3f} |  {: ^19}| {: ^18} format N/A self p_value N/A self test_statistic N/A self test_result N/A N/A self is_significant True False N/A s N/A _pretty_print_meta_data N/A N/A self dictionary N/A N/A N/A s N/A N/A k v N/A N/A dictionary items N/A N/A s N/A N/A N/A N/A N/A N/A N/A str k replace _ :  N/A str v N/A s N/A N/A chisq_test N/A N/A U degrees_freedom alpha N/A N/A N/A p_value N/A N/A N/A stats chi2 sf U degrees_freedom N/A N/A p_value N/A 1 alpha N/A N/A N/A True p_value N/A N/A N/A None p_value N/A two_sided_z_test N/A N/A Z alpha N/A N/A N/A p_value N/A 1 N/A N/A np max N/A N/A N/A stats norm cdf Z N/A 1 N/A N/A N/A stats norm cdf Z N/A N/A p_value N/A 1 N/A alpha 2.0 N/A N/A N/A True p_value N/A N/A N/A None p_value N/A