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    Polars DataFrame limit() Method

    Polars DataFrame limit() Method

    In Polars, the limit() method is used to retrieve a specific number of rows from a DataFrame. It functions similarly to SQL’s LIMIT clause, allowing you to restrict the number of rows returned from a DataFrame.

    In this article, I will explain the Polars DataFrame limit() method by using its syntax, parameters, usage, and how to return a new Polars DataFrame containing only the first n rows of the original DataFrame.

    Key Points –

    <a id="h-polars-dataframe-limit-introduction"></a>

    Polars DataFrame limit() Introduction

    Following is a syntax of the DataFrame.limit(). This function takes n params.

    
# Syntax of limit()
DataFrame.limit(n: int = 5) → DataFrame

    <a id="h-parameters-of-the-polars-dataframe-limit"></a>

    Parameters of the Polars DataFrame.limit()

    It allows only one parameter.

    <a id="h-return-value"></a>

    Return Value

    This function returns a new Polars DataFrame with at most n rows.

    <a id="h-usage-of-polars-dataframe-limit-method"></a>

    Usage of Polars DataFrame limit() Method

    The limit() method in Polars is used to restrict the number of rows returned from a DataFrame, similar to SQL's LIMIT clause. It is useful for previewing data, reducing computation time, and implementing pagination.

    To run some examples of the Polars DataFrame limit() method, let’s create a Polars DataFrame.

    
import polars as pl

technologies= {
    'Courses':["Spark", "PySpark", "Hadoop", "Python", "Pandas", "PySpark", "Java"],
    'Fee' :[22000, 25000, 23000, 24000, 26000, 30000, 35000],
    'Discount':[1000, 2300, 1000, 1200, 2500, 2000, 2200],
    'Duration':['35days', '40days', '65days', '50days', '60days', '30days', '45days']
          }

df = pl.DataFrame(technologies)
print("Original DataFrame:\n", df)

    Yields below output.

    To retrieve the first 5 rows of a DataFrame using Polars' limit() method (which defaults to 5), simply call limit() without any arguments.

    
# Using limit() without arguments (defaults to 5 rows)
df2= df.limit()
print("Last 5 rows of the DataFrame (default usage):\n", df2)

    Here,

    <a id="h-specifying-the-number-of-rows-using-limit-method"></a>

    Specifying the Number of Rows Using limit() Method

    You can specify the exact number of rows you want to retrieve using the limit(n) method, where n is the number of rows.

    
# Specifying the number of rows explicitly
df2 = df.limit(4) 
print(df2)

# Output:
# shape: (4, 4)
┌─────────┬───────┬──────────┬──────────┐
│ Courses ┆ Fee   ┆ Discount ┆ Duration │
│ ---     ┆ ---   ┆ ---      ┆ ---      │
│ str     ┆ i64   ┆ i64      ┆ str      │
╞═════════╪═══════╪══════════╪══════════╡
│ Spark   ┆ 22000 ┆ 1000     ┆ 35days   │
│ PySpark ┆ 25000 ┆ 2300     ┆ 40days   │
│ Hadoop  ┆ 23000 ┆ 1000     ┆ 65days   │
│ Python  ┆ 24000 ┆ 1200     ┆ 50days   │
└─────────┴───────┴──────────┴──────────┘

    Here,

    <a id="h-limiting-rows-dynamically"></a>

    Limiting Rows Dynamically

    You can dynamically set the number of rows to return using a variable. This is useful when the limit value is determined at runtime.

    
# Dynamically setting the limit
n = 3  # Change this value to limit rows dynamically
df2 = df.limit(n)
print(df2)

# Output:
# shape: (3, 4)
┌─────────┬───────┬──────────┬──────────┐
│ Courses ┆ Fee   ┆ Discount ┆ Duration │
│ ---     ┆ ---   ┆ ---      ┆ ---      │
│ str     ┆ i64   ┆ i64      ┆ str      │
╞═════════╪═══════╪══════════╪══════════╡
│ Spark   ┆ 22000 ┆ 1000     ┆ 35days   │
│ PySpark ┆ 25000 ┆ 2300     ┆ 40days   │
│ Hadoop  ┆ 23000 ┆ 1000     ┆ 65days   │
└─────────┴───────┴──────────┴──────────┘

    Here,

    <a id="h-combining-limit-with-filter-method"></a>

    Combining limit() with filter() Method

    You can use filter()to select specific rows based on a condition and then apply limit(n) to return only a subset of those filtered rows.

    
# Applying filter to select rows where Fee > 24000, then limit to 3 rows
df2 = df.filter(pl.col("Fee") > 24000).limit(3)
print(df2)

# Output:
# shape: (3, 4)
┌─────────┬───────┬──────────┬──────────┐
│ Courses ┆ Fee   ┆ Discount ┆ Duration │
│ ---     ┆ ---   ┆ ---      ┆ ---      │
│ str     ┆ i64   ┆ i64      ┆ str      │
╞═════════╪═══════╪══════════╪══════════╡
│ PySpark ┆ 25000 ┆ 2300     ┆ 40days   │
│ Pandas  ┆ 26000 ┆ 2500     ┆ 60days   │
│ PySpark ┆ 30000 ┆ 2000     ┆ 30days   │
└─────────┴───────┴──────────┴──────────┘

    Here,

    <a id="h-using-limit-with-select-method"></a>

    Using limit() with select() Method

    You can use select() to choose specific columns from the DataFrame and then apply limit(n) to restrict the number of rows returned.

    
# Selecting specific columns and limiting rows
df2 = df.select(["Courses", "Fee"]).limit(3)
print(df2)

# Output:
# shape: (3, 2)
┌─────────┬───────┐
│ Courses ┆ Fee   │
│ ---     ┆ ---   │
│ str     ┆ i64   │
╞═════════╪═══════╡
│ Spark   ┆ 22000 │
│ PySpark ┆ 25000 │
│ Hadoop  ┆ 23000 │
└─────────┴───────┘

    Here,

    <a id="h-conclusion"></a>

    Conclusion

    In conclusion, the limit() method in Polars is a powerful way to restrict the number of rows in a DataFrame. It is useful for previewing data, sampling, and optimizing performance when working with large datasets.

    Happy Learning!!

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    Related Articles

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    References