diff --git a/src/actionsheets/data/python/pandas/pandas.dataframe.toml b/src/actionsheets/data/python/pandas/pandas.dataframe.toml
index 7647ac4..a21bc4e 100644
--- a/src/actionsheets/data/python/pandas/pandas.dataframe.toml
+++ b/src/actionsheets/data/python/pandas/pandas.dataframe.toml
@@ -447,6 +447,10 @@ code = "data.rename(str.lower, axis='columns')"
 [derive.grow]
 section = "Grow"
 
+[derive.grow.col.fill]
+action = "Append column _col_ with constant value _v_"
+code = "?"
+
 [derive.grow.col.append]
 action = "Append column _col_ from series _s_"
 code = "df.assign(col=s)"
diff --git a/src/actionsheets/data/python/polars/polars.dataframe.toml b/src/actionsheets/data/python/polars/polars.dataframe.toml
index 3139e06..d51cc29 100644
--- a/src/actionsheets/data/python/polars/polars.dataframe.toml
+++ b/src/actionsheets/data/python/polars/polars.dataframe.toml
@@ -71,10 +71,22 @@ code = "pl.read_csv('file.csv')"
 [test]
 section = "Test"
 
+[test.inherits]
+action = "Is `pl.DataFrame` or subclass"
+code = "isinstance(x, pl.DataFrame)"
+
+[test.is]
+action = "Is `pl.DataFrame` but not subclass"
+code = "type(x) is pl.DataFrame"
+
 [test.empty]
 action = "Empty (no rows)"
 code = "data.is_empty()"
 
+[test.nempty]
+action = "Not empty (has rows)"
+code = "not data.is_empty()"
+
 [test.equal]
 action = "Data frames are equal"
 code = "data.equals(data2)"
@@ -154,6 +166,10 @@ data.group_by('patient').agg(
 )['dupe'].any()
 """
 
+[test.cols.duplicates]
+action = "Duplicates across two or more columns"
+code = "data.select('col1', 'col2').is_duplicated().any()"
+
 [test.col.type]
 action = "Column is of type"
 code = "data.schema['col1'] == dtype"
@@ -179,9 +195,13 @@ action = "Column is standard integer (64-bit)"
 code = "data.schema['age'] == pl.Int64"
 
 [test.col.type.float]
-action = "Columns is float"
+action = "Column is float"
 code = "data.schema['age'].is_float()"
 
+[test.col.type.date]
+action = "Column is date"
+code = "data.schema['date'].dtype == pl.Date"
+
 [test.col.type.list]
 action = "Column is list type"
 code = "data.schema['keywords'] == pl.List"
@@ -682,6 +702,13 @@ data.with_columns(
 """
 details = "`alias()` can be called after `pl.col()`, may be more readable sometimes"
 
+[derive.grow.col.multi.dict.constant]
+action = "Add multiple constant columns based on a dict"
+code = """
+for k, v in dict.items():
+    data = data.with_columns(pl.lit(v).alias(k))
+"""
+
 
 [derive.grow.int]
 section = "Integer column derivations"
diff --git a/src/actionsheets/data/python/polars/polars.series.toml b/src/actionsheets/data/python/polars/polars.series.toml
new file mode 100644
index 0000000..a260904
--- /dev/null
+++ b/src/actionsheets/data/python/polars/polars.series.toml
@@ -0,0 +1,490 @@
+language = "python"
+parent = "python.polars"
+name = "series"
+title = "Polars Series"
+code = "import polars as pl"
+
+
+[create]
+section = "Create"
+description = "Create a new Series"
+
+
+[create.empty]
+section = "Create empty series"
+
+[create.empty.object]
+action = "Empty series (of object type)"
+code = "pl.Series()"
+
+[create.empty.bool]
+action = "Empty boolean series"
+code = "pl.Series(dtype=pl.Boolean)"
+
+[create.empty.category.undefined]
+action = "Empty categorical series without defined categories"
+code = "pl.Series(dtype=pl.Categorical)"
+
+[create.empty.category]
+action = "Empty enum series"
+code = "pl.Series(dtype=pl.Enum(['a', 'b', 'c']))"
+
+[create.empty.int]
+action = "Empty int series"
+code = "pl.Series(dtype=pl.Int64)"
+
+[create.empty.float]
+action = "Empty float series"
+code = "pl.Series(dtype=pl.Float64)"
+
+[create.empty.date]
+action = "Empty date series"
+code = "pl.Series(dtype=pl.Date)"
+
+[create.empty.datetime]
+action = "Empty datetime series"
+code = "pl.Series(dtype=pl.Datetime)"
+
+[create.empty.list]
+action = "Empty list series"
+code = "pl.Series(dtype=pl.List)"
+
+
+[create.constant]
+section = "Create series of constant values"
+
+[create.constant.na]
+action = "Series of length _n_ filled with nulls"
+code = "pl.Series([None] * n)"
+
+[create.constant.value]
+action = "Constant value _v_ of length _n_"
+code = "pl.Series([v] * n)"
+
+
+[test]
+section = "Test"
+
+[test.inherits]
+action = "Is series or subclass"
+code = "isinstance(x, pl.Series)"
+
+[test.is]
+action = "Is series and not subclass"
+code = "type(x) is pl.Series"
+
+[test.empty]
+action = "Empty"
+code = "x.is_empty()"
+
+[test.nempty]
+action = "Not empty"
+code = "not x.is_empty()"
+
+[test.length]
+action = "Has length _n_"
+code = "len(x) == n"
+
+[test.type.bool]
+action = "Is boolean series"
+code = "x.dtype == pl.Boolean"
+
+[test.type.categorical]
+action = "Is categorical series"
+code = "x.dtype == pl.Categorical"
+
+[test.type.enum]
+action = "Is enum series"
+code = "x.dtype == pl.Enum"
+
+[test.type.numeric]
+action = "Is numeric series"
+code = "x.dtype.is_numeric()"
+details = "For example, pl.Int8 or pl.Float64"
+
+[test.type.int]
+action = "Is integer series"
+code = "x.dtype.is_integer()"
+
+[test.type.uint]
+action = "Is unsigned integer series"
+code = "x.dtype.is_unsigned_integer()"
+
+[test.type.float]
+action = "Is float series"
+code = "x.dtype.is_float()"
+
+[test.type.date]
+action = "Is date series"
+code = "x.dtype == pl.Date"
+
+[test.type.datetime]
+action = "Is datetime64 series"
+code = "x.dtype == pl.Datetime"
+
+[test.type.str]
+action = "Is string series"
+code = "x.dtype == pl.String"
+
+[test.type.list]
+action = "Is list series"
+code = "x.dtype == pl.List"
+
+[test.type.nested]
+action = "Is nested series (struct or list)"
+code = "x.dtype.is_nested()"
+
+
+[test.duplicate.none]
+action = "No duplicate elements (all unique)"
+code = "x.is_unique().all()"
+
+[test.duplicate.any]
+action = "Any duplicate elements"
+code = "x.is_duplicated().any()"
+
+[test.contains.null]
+action = "Contains null"
+code = "x.has_nulls()"
+
+[test.contains.null.all]
+action = "Contains only nulls"
+code = "x.is_null().all()"
+
+[test.contains.null.none]
+action = "Contains no nulls"
+code = "not x.has_nulls()"
+
+[test.contains.'nan']
+action = "Contains NaN"
+code = "x.is_nan().any()"
+
+[test.contains.'nan'.none]
+action = "Contains no NaNs"
+code = "x.is_not_nan().all()"
+
+[test.contains.'inf']
+action = "Contains infinity"
+code = "x.is_infinite().any()"
+
+[test.contains.finite.all]
+action = "Contains only finite values"
+code = "x.is_finite().all()"
+
+[test.contains.value]
+action = "Contains value _v_, ignoring nulls"
+code = "v in x"
+
+[test.contains.values]
+action = "Contains any of the values _v1_, _v2_, ignoring nulls"
+code = "x.is_in([v1, v2]).any()"
+
+[test.missing.value]
+action = "Does not contain value _v_"
+code = "v not in x"
+
+
+[test.order.increasing]
+action = "Are elements in increasing order"
+code = "x.is_sorted()"
+details = "Presence of nulls can lead to unexpected behavior, as they need to come first."
+
+[test.order.decreasing]
+action = "Are elements in decreasing order"
+code = "x.is_sorted(descending=True)"
+details = "Presence of nulls can lead to unexpected behavior, as they need to come first."
+
+
+[test.bool]
+section = "Test boolean series"
+
+[test.bool.'true'.all]
+action = "All values are True"
+code = "x.all()"
+
+[test.bool.'false'.all]
+action = "All values are False"
+code = "not x.any()"
+
+
+[test.str]
+section = "Tests for string series"
+
+[test.str.contains]
+action = "Contains string _s_"
+code = "x.str.contains(s).any()"
+
+
+[extract]
+section = "Extract"
+
+[extract.length]
+action = "Number of elements"
+code = "len(x)"
+
+[extract.hash]
+action = "Hash"
+code = "hash(tuple(x))"
+
+[extract.dtype]
+action = "Data type (dtype)"
+code = "x.dtype"
+
+[extract.nunique]
+action = "Number of unique elements, ignoring nulls"
+code = "x.n_unique()"
+
+[extract.min]
+action = "Smallest value, ignoring nulls"
+code = "x.min()"
+
+[extract.max]
+action = "Greatest value, ignoring nulls"
+code = "x.max()"
+
+[extract.min.index]
+action = "Index of the smallest value, ignoring NAs"
+code = "x.arg_min()"
+
+[extract.max.index]
+action = "Index of the greatest value, ignoring NAs"
+code = "x.arg_max()"
+
+[extract.value.counts]
+action = "Count occurrence per value"
+code = "x.value_counts()"
+
+
+[extract.type]
+section = "Type-specific operations"
+
+
+[extract.type.enum]
+section = "Enum"
+
+
+[extract.type.cat]
+section = "Categorical"
+
+[extract.type.cat.categories]
+action = "Get categories"
+code = "x.cat.get_categories()"
+
+
+[extract.type.str]
+section = "String"
+
+
+[extract.type.list]
+section = "List"
+
+[extract.type.list.length]
+action = "Get length of each list element"
+code = "x.list.len()"
+
+[extract.type.list.item]
+action = "Get the _i_th item of each list element"
+code = "x.list[i]"
+
+
+[extract.type.struct]
+section = "Struct"
+
+
+[derive]
+section = "Derive"
+
+
+[derive.order]
+section = "Order"
+
+[derive.order.reverse]
+action = "Reverse"
+code = "x.reverse()"
+
+[derive.order.sort.asc]
+action = "Sort ascendingly"
+code = "x.sort()"
+details = "Nulls are placed first"
+
+[derive.order.sort.desc]
+action = "Sort descendingly"
+code = "x.sort(descending=True)"
+details = "Nulls are placed first"
+
+[derive.order.shuffle]
+action = "Shuffle"
+code = "x.shuffle()"
+
+
+[derive.transform]
+section = "Transform"
+
+[derive.transform.mask]
+section = "Mask"
+
+[derive.transform.mask.duplicate]
+action = "Duplicate mask"
+code = "x.is_duplicated()"
+
+[derive.transform.fill.null]
+action = "Fill null by value_v_"
+code = "x.fill_null(value=v)"
+
+[derive.transform.fill.'nan']
+action = "Fill NaN by value_v_"
+code = "x.fill_nan(value=v)"
+
+[derive.transform.replace.value.null]
+action = "Replace value _v_ by null"
+code = "x.replace(v, None)"
+
+[derive.transform.replace.value]
+action = "Replace value _v_ by _w_"
+code = "x.replace(v, w)"
+
+[derive.transform.map]
+action = "Map all values"
+code = """
+x = pl.Series([1, 2, 3])
+x.replace_strict([1, 2, 3], [10, -2, -3])
+"""
+
+[derive.transform.map.dict]
+action = "Map all values using a `dict`"
+code = """
+x = pl.Series([1, 2, 3])
+x.replace_strict({1: 10, 2: -2, 3: -3})
+"""
+
+
+[derive.transform.cast]
+section = "Cast to type"
+
+[derive.transform.cast.bool]
+action = "Cast to boolean"
+code = "x.cast(bool)"
+
+[derive.transform.cast.numeric]
+action = "Cast series to numeric dtype"
+code = "x.cast(float)"
+
+[derive.transform.cast.int]
+action = "Cast to integer"
+code = "x.cast(int)"
+
+[derive.transform.cast.float]
+action = "Cast to float"
+code = "x.cast(float)"
+
+[derive.transform.cast.str]
+action = "Cast to string"
+code = "x.cast(str)"
+
+[derive.transform.cast.cat]
+action = "Cast to categorical"
+code = "x.cast(str).cast(pl.Categorical)"
+
+[derive.transform.cast.enum]
+action = "Cast to enum"
+code = "x.cast(pl.Enum)"
+
+[derive.transform.cast.cat.int]
+action = "Cast categorical to integer codes"
+code = "x.to_physical()"
+
+[derive.transform.cast.enum.int]
+action = "Cast enum to integer codes"
+code = "x.to_physical()"
+
+
+[derive.grow]
+section = "Grow"
+
+
+[derive.shrink]
+section = "Shrink"
+
+[derive.shrink.head]
+action = "First _n_ elements"
+code = "x.head(n)"
+
+[derive.shrink.tail]
+action = "Last _n_ elements"
+code = "x.tail(n)"
+
+[derive.shrink.slice]
+action = "Slice"
+code = "x[a:b]"
+
+[derive.shrink.subset]
+action = "Select _n_ elements starting from index _i_"
+code = "x.slice(i, n)"
+
+[derive.shrink.indices]
+action = "Keep indices"
+code = "x.gather([1, 3])"
+
+[derive.shrink.indices.step]
+action = "Keep every _n_th element, starting from index _i_"
+code = "x.gather_every(n, i)"
+
+[derive.shrink.sample]
+action = "Sample _n_ elements"
+code = "x.sample(n)"
+
+[derive.shrink.null]
+action = "Drop null elements"
+code = "x.drop_nulls()"
+
+[derive.shrink.'nan']
+action = "Drop NaN elements"
+code = "x.drop_nans()"
+
+[derive.shrink.top]
+action = "Keep _n_ largest elements"
+code = "x.top_k(n)"
+
+[derive.shrink.bottom]
+action = "Keep _n_ smallest elements"
+code = "x.bottom_k(n)"
+
+[derive.shrink.duplicates]
+action = "Remove duplicates"
+code = "x.unique()"
+
+
+[derive.combine]
+section = "Combine"
+
+[derive.combine.concat]
+action = "Append another series"
+code = "x.append(y)"
+
+
+
+[convert]
+section = "Convert"
+
+[convert.list]
+action = "To list"
+code = "x.to_list()"
+
+[convert.list.2]
+code = "list(x)"
+
+[convert.numpy]
+action = "To numpy array"
+code = "x.to_numpy()"
+
+[convert.dataframe]
+action = "To Polars data frame with single column"
+code = "x.to_frame('col1')"
+
+[convert.str]
+action = "To instantiatable string representation"
+code = "x.to_init_repr()"
+
+[convert.dummy]
+action = "Dummy encoding of values (as data frame)"
+code = "x.to_dummies()"
diff --git a/src/actionsheets/data/python/polars/polars.types.toml b/src/actionsheets/data/python/polars/polars.types.toml
new file mode 100644
index 0000000..3fddce5
--- /dev/null
+++ b/src/actionsheets/data/python/polars/polars.types.toml
@@ -0,0 +1,76 @@
+language = "python"
+parent = "python.polars"
+name = "types"
+title = "Polars Types"
+code = "import polars as pl"
+
+
+[enum]
+section = "Enum"
+
+
+[enum.create]
+section = "Create"
+
+[enum.create.define]
+action = "Define enum"
+code = "pl.Enum(['a', 'b', 'c'])"
+
+[enum.create.literal]
+action = "Create enum from Literal"
+code = """
+from typing import Literal
+Labels = Literal['a', 'b', 'c']
+pl.Enum(Labels.__args__)
+"""
+
+
+[enum.extract]
+section = "Extract"
+
+[enum.extract.categories]
+action = "Get the enum categories"
+code = "x.categories"
+
+
+[list]
+section = "List"
+description = "Variable-length list elements"
+
+[list.create]
+section = "Create"
+
+[list.create.undefined]
+action = "List with undefined inner elements type"
+code = "pl.List"
+
+[list.create.bool]
+action = "List of booleans"
+code = "pl.list(bool)"
+
+[list.create.int]
+action = "List of integers"
+code = "pl.list(int)"
+
+[list.create.float]
+action = "List of floats"
+code = "pl.list(float)"
+
+[list.create.string]
+action = "List of strings"
+code = "pl.list(str)"
+
+[list.test]
+section = "Test"
+
+[list.test.int]
+action = "Test if type is list of numeric elements"
+code = "x.inner.is_numeric()"
+
+
+[list.extract]
+section = "Extract"
+
+[list.extract.type]
+action = "Get inner elements type"
+code = "x.inner"