Pandas In Moonbit

mooncakes.io link: https://mooncakes.io/docs/smallbearrr/pandas

moonbit-community link: https://github.com/moonbit-community/pandas

Introduction

This is a data processing library written in Moonbit. It provides a DataFrame data structure for efficient data manipulation and analysis.

Features

• DataFrame and Series data structures for handling tabular data
• Support for various data types including integers, floats, strings, and booleans
• Basic data manipulation operations such as filtering, sorting, and aggregating
• Support for reading and writing CSV files
• Support for handling missing values and null data
• Support for mathematical operations on Series and DataFrames

Installation

To install the package, run the following command in the terminal:

moon add smallbearrr/pandas

Dependencies

This package depends on the following libraries:

• "moonbitlang/x/fs": A file system I/O library.
• "xunyoyo/NyaCSV": A CSV parsing library.

To install these dependencies, run the following command:

moon add moonbitlang/x
moon add xunyoyo/NyaCSV

Usage

DataFrame

create a DataFrame

let col1 = Series::new("A", SeriesInput::Int32([1, 2, 3]))
let col2 = Series::new("B", SeriesInput::Float32([1.5, 2.5, 3.5]))
let col3 = Series::new("C", SeriesInput::Int32_Nullable([Some(1), None, Some(3)]))
let df = DataFrame::new([col1, col2, col3])

Display the first few(min(size, 5)) rows of the DataFrame

df.head()

DataFrame already traits the Show, it can print the DataFrame directly:

println(df)

Add a new column

let new_col = Series::new("C", SeriesInput::Bool([true, false, true]))
df.add_column!(new_col)

Drop a column

df.drop_column!("C")

Rename a column

df.rename!("A", "A1")

Select a column

let df_col = df.column("A")

Select specific columns

let df_cols = df.select_columns!(["A1", "B"])

Drop a row

df.drop_row!(0)

Add a new row

df.add_row!([SeriesValue::Int32(7), SeriesValue::Float32(7.5), SeriesValue::Bool(true), SeriesValue::Str("ok")])

Select rows by range or by specific indices:

let row_selected_range = df.select_rows!(range=(1, 3))
let row_selected_indices = df.select_rows!(indices=[1, 3, 5])

Filter rows based on a condition applied to a specific column:

let filtered = df.filter!("A", fn(x) -> Bool { x < DType::Int(3) })

Sort the DataFrame by a specified column in ascending or descending order:

df.sort!("A")
df.sort!("B", descending=true)

Convert Between DataFrame and @NyaCSV.CSV:

let df = DataFrame::from_NyaCSV(csv)
let csv = df.to_NyaCSV()

Read a CSV file:

let df = DataFrame::read_csv!("./data.csv")

Write the DataFrame to a CSV file:

df.write_csv!("./output.csv")

Series

Create a Series

let series_int = Series::new("IntColumn", SeriesInput::Int32([1, 2, 3]))
let series_float = Series::new("FloatColumn", SeriesInput::Float32([1.1, 2.2, 3.3]))
let series_bool = Series::new("BoolColumn", SeriesInput::Bool([true, false, true]))
let series_str = Series::new("StrColumn", SeriesInput::Str(["a", "b", "c"]))

Erase element

series.erase(1)

Sort the SeriesData in Series and return the indices of the sorted elements

let indices = series.sort()

Add two Series

let series1 = Series::new("A", SeriesInput::Int32([1, 2, 3]))
let series2 = Series::new("B", SeriesInput::Float32([1.5, 2.0, 3.5]))
let add = series1 + series2

Operation of add, subtract, multiply and divide

let add_op = series1 + series2
let sub_op = series1 - series2
let mul_op = series1 * series2
let div_op = series1 / series2

Feature

DataFrame Methods

Method	Description
new	Create a new DataFrame
shape	Get the shape of the DataFrame
data	Get the data of the DataFrame
head	Display the first few rows of the DataFrame
add_column	Add a new column to the DataFrame
drop_column	Drop a column from the DataFrame
rename	Rename a column in the DataFrame
column	Select a column from the DataFrame
select_columns	Select specific columns from the DataFrame
drop_row	Drop a row from the DataFrame
add_row	Add a new row to the DataFrame
select_rows	Select specific rows from the DataFrame
filter	Filter rows in the DataFrame based on a condition
sort	Sort the DataFrame by a specified column
vstack	Vertically stack two DataFrames
hstack	Horizontally stack two DataFrames
clear	Clear all data in the DataFrame
clone	Create a deep copy of the DataFrame
item	Retrieve a single item from the DataFrame
limit	Create a new DataFrame containing only the first N rows
tail	Create a new DataFrame containing only the last N rows
slice	Create a new DataFrame containing a slice of rows
to_series	Convert a column of the DataFrame to a Series
unique	Remove duplicate rows from the DataFrame
replace_column	Replace a column in the DataFrame
reverse	Reverse the order of rows in the DataFrame
get_column_index	Get the index of a column by its name
with_row_index	Add a row index column to the DataFrame
transpose	Transpose the DataFrame over the diagonal
mean	Calculate the mean of each column in the DataFrame
var	Calculate the variance of each column in the DataFrame
count	Count the number of rows and columns in the DataFrame
max	Get the maximum value of each column in the DataFrame
max_horizontal	Get the maximum value of each row in the DataFrame
min	Get the minimum value of each column in the DataFrame
min_horizontal	Get the minimum value of each row in the DataFrame
sum	Calculate the sum of each column in the DataFrame
sum_horizontal	Calculate the sum of each row in the DataFrame
dtypes	Get the data types of each column in the DataFrame
height	Get the number of rows in the DataFrame
width	Get the number of columns in the DataFrame
product	Calculate the product of each column in the DataFrame
schema	Get the schema of the DataFrame
is_empty	Return whether the DataFrame is empty
fill_null	Fill null values using the specified value or strategy
null_count	Return the number of null values in the DataFrame
cast	Cast DataFrame column(s) to the specified dtype(s)
to_dict	Convert the DataFrame to a dictionary
to_init_repr	Convert DataFrame to instantiable string representation
drop_nulls	Drop all rows that contain null values
gather_every	Take every nth row in the DataFrame and return as a new DataFrame
drop_in_place	Drop a single column in-place and return the dropped column
read_csv	Read a CSV file and convert it into a DataFrame
from_NyaCSV	Convert a NyaCSV.CSV object into a DataFrame
to_NyaCSV	Convert the DataFrame to a NyaCSV.CSV object
write_csv	Write the DataFrame to a CSV file

Series Methods

Method	Description
new	Create a new Series
data	Get the data of the Series
erase	Erase an element from the Series
sort	Sort the SeriesData in Series and return the indices of the sorted elements
+	Add two Series
-	Subtract two Series
*	Multiply two Series
/	Divide two Series
mean	Calculate the mean of the Series
var	Calculate the variance of the Series
argsort	Return the indices that would sort the Series
copy	Create a copy of the Series
count	Count the number of elements in the Series
get_type	Get the type of the Series
max	Get the maximum value of the Series
merge	Merge two Series
min	Get the minimum value of the Series
name	Get the name of the Series
reverse	Reverse the order of elements in the Series
sum	Calculate the sum of the Series
abs	Return a new Series with the absolute value of each element
acos	Return a new Series with the arccos of each element
all	Return whether all non-null elements in the Series are true
any	Return whether any non-null element in the Series is true
append	Append another Series to the current one and return a new Series
clear	Remove all elements from the current Series
concat	Concatenate multiple Series and return the result
cos	Return a new Series with the cosine of each element
extend	Extend the current Series in-place with another Series
has_null	Check if the current Series contains any null values
is_empty	Check if the current Series is empty
is_not_null	Return a boolean Series indicating non-null elements
is_null	Return a boolean Series indicating null elements
is_sorted	Check if the current Series is sorted
length	Return the length of the current Series
log	Return a new Series with the logarithm of each element
log10	Return a new Series with the base-10 log of each element
lower_bound	Return a new Series with each element replaced by the lower bound
n_unique	Return the number of unique elements in the Series
not_	Return the logical NOT of a boolean Series
null_count	Return the count of null values in the Series
op_get	Return the element at a given index in the Series
sin	Return a new Series with the sine of each element
tan	Return a new Series with the tangent of each element
unique_counts	Return a new Series showing the count of each unique value
upper_bound	Return a new Series with each element replaced by the upper bound
slice	Return a new Series containing elements in the specified range
swap	Swap two elements in the Series
get_argsort_indices	Get the indices that would sort the Series
move_nulls_front	Move null values to the front of the Series
move_nulls_back	Move null values to the back of the Series

Contributing

Issues and pull requests are welcome. Please make sure to run all tests before submitting.

Contact

If you have questions, feel free to open an issue in the repository. For other inquiries, contact me via email: [[email protected]].

License

This project is licensed under the Apache-2.0 License. See the LICENSE file for details.