fenn.tabular

fenn.tabular.array_summary(arr)[source]

NumPy-oriented helper for shape, dtype, basic stats, and NaN checks on ndarray.

Parameters:

arr (ndarray)

Return type:

DataFrame

fenn.tabular.corr_overview(df, top_n=10)[source]

Compute correlations between numeric columns and return the strongest pairs as a tidy table.

Parameters:

  • df (DataFrame)

  • top_n (int)

Return type:

DataFrame

fenn.tabular.missing_report(df)[source]

Compact report of missing values per column, percentage, and flags for all-null or almost-all-null columns.

Parameters:

df (DataFrame)

Return type:

DataFrame

fenn.tabular.numeric_profile(df, clip_quantile=None)[source]

Describe numeric columns only (min, max, mean, std, quantiles) with optional clipping of extreme quantiles.

Parameters:

  • df (DataFrame)

  • clip_quantile (float | None)

Return type:

DataFrame

fenn.tabular.quick_sample(df, n=5, columns=None, seed=None)[source]

Convenience wrapper around head/random sampling, with optional column subset and seed.

Parameters:

  • df (DataFrame)

  • n (int)

  • columns (list | None)

  • seed (int | None)

Return type:

DataFrame

fenn.tabular.summary(df)[source]

One-shot overview combining shape, dtypes, basic stats, missing value counts, and cardinality info for categorical columns.

Parameters:

df (DataFrame)

Return type:

DataFrame

fenn.tabular.unique_report(df)[source]

Show number of unique values per column and, for low-cardinality columns, a small frequency table.

Parameters:

df (DataFrame)

Return type:

DataFrame