Moving between R and Python

The Python and R packages share analytical concepts and function names wherever the languages permit. The goal is familiar workflows, not byte-for-byte API identity.

Common conventions

Concept	Python	R
Package alias	import vivainsights as vi	library(vivainsights)
Output selector	return_type="table"	return="table"
Data frame	pandas.DataFrame	data.frame or tibble
Plot	Matplotlib, Seaborn, or Plotly object	ggplot object
Missing value	None or numpy.nan	NULL or NA

Python uses return_type because return is a reserved keyword. Supported values are documented per function and generally mirror the corresponding R function.

Shared analytical functions

The following established functions have direct or close counterparts:

Analysis family	Python and R function names
Core visualizations	create_bar, create_boxplot, create_bubble, create_line, create_rank, create_trend
Specialized visualizations	create_inc, create_lorenz, create_radar, create_sankey, create_survival
Data validation	check_query, extract_date_range, extract_hr, hrvar_count
Segmentation	identify_churn, identify_holidayweeks, identify_inactiveweeks, identify_outlier, identify_usage_segments
Network analysis	network_g2g, network_p2p, network_summary
Data access	import_query, load_pq_data, load_g2g_data, load_p2p_data

The R package may contain newer functions that have not yet been implemented in Python. Check the R reference and the Python reference for the current surfaces.

Equivalent example

Python:

import vivainsights as vi

data = vi.load_pq_data()
result = vi.create_bar(
    data,
    metric="Collaboration_hours",
    hrvar="Organization",
    return_type="table",
)

R:

library(vivainsights)

data <- pq_data
result <- create_bar(
  data,
  metric = "Collaboration_hours",
  hrvar = "Organization",
  return = "table"
)

Intentional differences

• Python follows Python naming and keyword rules.

• Plot object types differ between ecosystems.

• Python functions generally return pandas objects; R functions generally return data frames or tibbles.

• A function available in one package may arrive later in the other.

When porting an analysis, first match the function’s analytical purpose and selected columns, then account for these language-specific differences.