I am trying to add another column that will contain combination of two columns (Total & percentage) into a result column(labels_value) which look like: (Total) percentage%. Basically to wrap bracket strings on Total column and add % string at the end of combination of these two columns. df import polars as pl so_df = pl.DataFrame( [{'Flag': 'Outof Range', 'Category': 'Thyroid', 'len': 7, 'Total': 21, 'percentage': 33.33, 'value': 33.33}, {'Flag': 'Outof Range', 'Category': 'Inflammatory Marker', 'len': 2, 'Total': 8, 'percentage': 25.0, 'value': 25.0}, {'Flag': 'Outof Range', 'Category': 'Lipid', 'len': 12, 'Total': 63, 'percentage': 19.05, 'value': 19.05}, {'Flag': 'Outof Range', 'Category': 'LFT', 'len': 14, 'Total': 87, 'percentage': 16.09, 'value': 16.09}, {'Flag': 'Outof Range', 'Category': 'DLC', 'len': 11, 'Total': 126, 'percentage': 8.73, 'value': 8.73}, {'Flag': 'Outof Range', 'Category': 'Vitamin', 'len': 1, 'Total': 14, 'percentage': 7.14, 'value': 7.14}, {'Flag': 'Outof Range', 'Category': 'CBC', 'len': 2, 'Total': 45, 'percentage': 4.44, 'value': 4.44}, {'Flag': 'Outof Range', 'Category': 'KFT', 'len': 2, 'Total': 56, 'percentage': 3.57, 'value': 3.57}, {'Flag': 'Outof Range', 'Category': 'Urine Examination', 'len': 1, 'Total': 28, 'percentage': 3.57, 'value': 3.57}, {'Flag': 'Within Range', 'Category': 'Thyroid', 'len': 14, 'Total': 21, 'percentage': 66.67, 'value': -66.67}, {'Flag': 'Within Range', 'Category': 'Inflammatory Marker', 'len': 6, 'Total': 8, 'percentage': 75.0, 'value': -75.0}, {'Flag': 'Within Range', 'Category': 'Lipid', 'len': 51, 'Total': 63, 'percentage': 80.95, 'value': -80.95}, {'Flag': 'Within Range', 'Category': 'LFT', 'len': 73, 'Total': 87, 'percentage': 83.91, 'value': -83.91}, {'Flag': 'Within Range', 'Category': 'DLC', 'len': 115, 'Total': 126, 'percentage': 91.27, 'value': -91.27}, {'Flag': 'Within Range', 'Category': 'Vitamin', 'len': 13, 'Total': 14, 'percentage': 92.86, 'value': -92.86}, {'Flag': 'Within Range', 'Category': 'CBC', 'len': 43, 'Total': 45, 'percentage': 95.56, 'value': -95.56}, {'Flag': 'Within Range', 'Category': 'KFT', 'len': 54, 'Total': 56, 'percentage': 96.43, 'value': -96.43}, {'Flag': 'Within Range', 'Category': 'Urine Examination', 'len': 27, 'Total': 28, 'percentage': 96.43, 'value': -96.43}, {'Flag': 'Within Range', 'Category': 'Anemia', 'len': 38, 'Total': 38, 'percentage': 100.0, 'value': -100.0}, {'Flag': 'Within Range', 'Category': 'Diabetes', 'len': 22, 'Total': 22, 'percentage': 100.0, 'value': -100.0}, {'Flag': 'Within Range', 'Category': 'Electrolyte', 'len': 46, 'Total': 46, 'percentage': 100.0, 'value': -100.0}] )  shape: (21, 6) Flag Category len Total percentage value str str i64 i64 f64 f64 "Outof Range" "Thyroid" 7 21 33.33 33.33 "Outof Range" "Inflammatory Marker" 2 8 25.0 25.0 "Outof Range" "Lipid" 12 63 19.05 19.05 "Outof Range" "LFT" 14 87 16.09 16.09 "Outof Range" "DLC" 11 126 8.73 8.73 … … … … … … "Within Range" "KFT" 54 56 96.43 -96.43 "Within Range" "Urine Examination" 27 28 96.43 -96.43 "Within Range" "Anemia" 38 38 100.0 -100.0 "Within Range" "Diabetes" 22 22 100.0 -100.0 "Within Range" "Electrolyte" 46 46 100.0 -100.0  I have tried below three ways and none of them worked: (so_df # .with_columns(labels_value = "("+str(pl.col("Total"))+") "+str(pl.col("percentage"))+"%") # .with_columns(labels_value = "".join(["(",str(pl.col("Total")),") ",str(pl.col("percentage")),"%"])) # .with_columns(labels_value =pl.concat_str([pl.col("Total"),pl.col("percentage")])))  Desired Result would be like: (21) 33.33% # 1st row of labels_value column (8) 25% (63) 19.05% . . 
Here are a few options: so_df.with_columns( labels_value_1=pl.format("({}) {}%", "Total", "percentage"), labels_value_2=pl.concat_str( pl.lit("("), "Total", pl.lit(") "), "percentage", pl.lit("%") ), labels_value_3=( "(" + pl.col("Total").cast(pl.String) + ") " + pl.col("percentage").cast(pl.String) + "%" ), ) # Only Total, percentage and outputs shown for brevity # ┌───────┬────────────┬────────────────┬────────────────┬────────────────┐ # │ Total ┆ percentage ┆ labels_value_1 ┆ labels_value_2 ┆ labels_value_3 │ # │ --- ┆ --- ┆ --- ┆ --- ┆ --- │ # │ i64 ┆ f64 ┆ str ┆ str ┆ str │ # ╞═══════╪════════════╪════════════════╪════════════════╪════════════════╡ # │ 21 ┆ 33.33 ┆ (21) 33.33% ┆ (21) 33.33% ┆ (21) 33.33% │ # │ 8 ┆ 25.0 ┆ (8) 25.0% ┆ (8) 25.0% ┆ (8) 25.0% │ # │ 63 ┆ 19.05 ┆ (63) 19.05% ┆ (63) 19.05% ┆ (63) 19.05% │ # │ 87 ┆ 16.09 ┆ (87) 16.09% ┆ (87) 16.09% ┆ (87) 16.09% │ # │ 126 ┆ 8.73 ┆ (126) 8.73% ┆ (126) 8.73% ┆ (126) 8.73% │ # │ … ┆ … ┆ … ┆ … ┆ … │ # │ 56 ┆ 96.43 ┆ (56) 96.43% ┆ (56) 96.43% ┆ (56) 96.43% │ # │ 28 ┆ 96.43 ┆ (28) 96.43% ┆ (28) 96.43% ┆ (28) 96.43% │ # │ 38 ┆ 100.0 ┆ (38) 100.0% ┆ (38) 100.0% ┆ (38) 100.0% │ # │ 22 ┆ 100.0 ┆ (22) 100.0% ┆ (22) 100.0% ┆ (22) 100.0% │ # │ 46 ┆ 100.0 ┆ (46) 100.0% ┆ (46) 100.0% ┆ (46) 100.0% │ # └───────┴────────────┴────────────────┴────────────────┴────────────────┘  pl.format I would say is most idiomatic, and it does the casting to string for you (much like Python's f-strings). It uses {} as a placeholder. This is what I'd personally recommend out of the options presented. For concat_str, you can add the parentheses and "%" with pl.lit (strings are parsed as column names in this function). It will cast numeric columns to string for you. Lastly, string concatenation with the + operator does work, but you must cast the column(s) with Polars' .cast method, rather than Python's builtin str. One thing to note is that row 2 of the output does differ slightly from your desired output. (8) 25% (expected) vs (8) 25.0% (actual). This is because the string representation of floating point columns in Polars contain at least one decimal place. If that is an issue, drop a comment and I will try to come up with a solution.