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simpler-reshape's Introduction

NAME

SimpleR::Reshape

Reshape data like R : read.table, write.table, merge, reshape2, dplyr

数据处理转换,接口山寨自R语言

TOOL

split_file.pl

split_file.pl -f xxx.csv -l 500 -t yyy

split_file.pl -f xxx.csv -i 0 -s ',' -t yyy

merge_file.pl

big.csv left join small.csv

perl merge_file.pl -f small.csv -k 1 -v 0,2 -F big.csv -K 0 -V 0,1,2,3 -o merge.csv

FUNCTION

example : xt/ 实例参考 xt 子文件夹

read_table

data : csv / arrayref / hashref , dim 2, 二维数据表

input data -> filter (skip_sub) -> select / transform / mutate (conv_sub) -> output

输入 数据 -> 过滤 行(skip_sub) -> 抽取/转换/新增 列 (conv_sub) -> 输出

csv / arrayref data: row is $arrayref, hashref data : row is ($k, $v)

my $df = 'reshape_src.csv';
my $r = read_table($df, 
    #sep=>',', 
    charset=>'utf8', 

    #skip_head=>0, 
    skip_sub => sub {
        my ($r) = @_;        # csv or arrayref
        # my ($k, $v) = @_;  # hashref

        $r->[3]<200 
        }, 

    conv_sub => sub { 
        my ($r) = @_;        # csv or arrayref
        # my ($k, $v) = @_;  # hashref

        [ "$r->[0] $r->[1]", $r->[2], $r->[3] ] 
        }, 

    #write_head => [ "head_a", "key" , "value" ], 
    #return_arrayref => 1, 
    write_file => '01.read_table.csv', 
);

write_table

write data into csv 将指定数据写入文本文件

my $d = [ [qw/a b 1/], [qw/c d 2/] ]; 
write_table($d, 
    file=> 'write_table.csv', 
    #sep => ',', 
    head => [ 'ka', 'kb', 'cnt'], 
    charset => 'utf8', 
);

melt

melt data like R reshape2

原始数据按id聚合,然后把measure的多个列映射成key-value对

#id / measure => [ 1, 2, 'somekey', sub { ... }, ], 4, 'somekey', sub { ... }

my $r = melt('reshape_src.csv',
    #sep=>',', 
    charset => 'utf8', 
    skip_head => 1, 
    #skip_sub => sub { $_[0][3]<1000 }, 

    names => [ qw/day hour state cnt rank/ ], 
    id => [ 0, 1, 2 ],
    measure => [3, 4], 
    #measure_names => [qw/.../], 

    write_head => [ qw/day hour state key value/ ], 
    return_arrayref => 1, 
    melt_file => '02.melt.1.csv',
);

melt('reshape_src.csv',
    skip_head => 1, 

    #names => [ qw/day hour state cnt rank/ ], 
    id => [ sub { "$_[0][0]d $_[0][1]h" } , 2 , 'test' ],
    measure => [ 3, 4, sub { $_[0][3] * $_[0][4] } ], 
    measure_names => [qw/cnt rank cxr/], 

    write_head => [ qw/dayhour state somehead key value/ ], 
    melt_file => '02.melt.2.csv',
);

cast

cast data like R reshape2,原始数据按id聚合,根据指定的 measure(key) 分组,统计value

reduce_sub : process data when read each row,在读取每一行数据的过程中,顺便处理value

stat_sub : process data after read all rows,在数据全部读取完毕后,对value列表进行最终统计

id : same as melt, 与melt相同

measure/value : return 1 value,返回单个标量

my $r = cast('02.melt.csv', 
        #sep => ',', 

        #key 有 cnt / rank 两种
        names => [ qw/day hour state key value/ ], 
        id => [ 0, 1, 2 ],
        measure => 3, 
        value => 4, 
        
        reduce_sub => sub { my ($last, $now) = @_; return $last+$now; }, 
        #reduce_start_value => 0, 

        write_head => 1, 

        default_cell_value => 0,
        #default_cast_value => 0, 

        cast_file => '03.cast.1.csv', 
        return_arrayref => 1, 
    );

    cast('02.melt.csv', 
        sep => ',', 

        #names => [ qw/day hour state key value/ ], #key 有 cnt / rank 两种
        id => [ sub { "$_[0][0] $_[0][1]" }, 2 ],
        id_names => [ qw/dayhour state/ ],
        measure => 3, 
        measure_names => [ qw/rank cnt/ ],
        value => 4, 

        stat_sub => sub { my ($r) = @_; (sort { $b<=> $a } @$r)[0] }, 
        default_cell_value => 0,

        write_head => 1, 
        cast_file => '03.cast.2.csv', 
        return_arrayref => 0, 
    );

merge

merge 2 dataframe, 合并两个dataframe,在perl中是二层数组

my $r = merge( 
    [ [qw/a b 1/], [qw/c d 2/] ], 
    [ [qw/a b 3/], [qw/c d 4/] ], 
    by => [ 0, 1], 
    value => [2], 
);
# $r = [["a", "b", 1, 3], ["c", "d", 2, 4]]

merge_file

merge 2 txt file, 合并两个文本文件

$big left join $small with some columns data

my $merge_fname = merge_file( 
    $small,
    $big, 

    merge_file => "$big.merge.csv", 
    by_x => [ 1 ], 
    value_x => [0, 2], 
    by_y => [ 0 ], 
    value_y => [ 0, 1, 2, 3 ], 
);

split_file

split large file by some columns or line count

把一个大文件按指定id或行数拆分成多个小文件

my $src_file = '06.split_file.log';

split_file($src_file, id => [ 0 ] ,
    # sep => ',', 
    # split_file => '06.test.log', 
);

split_file($src_file, line_cnt => 400);

arrange

sort rows by some method

按指定方法,将所有数据按行重新排序

my $r = arrange('reshape_src.csv', 
    skip_head => 1, 
    sep=> ',', 
    charset => 'utf8', 

    arrange_sub => sub { 
        $a->[4] <=> $b->[4] or
        $a->[3] <=> $b->[3] 
    }, 
    arrange_file => '07.arrange.csv', 
    return_arrayref => 1, 
    write_head => [ qw/day hour state cnt rank/ ], 
);

map_cast_col

stat column, then map column with the stat value

按指定方法统计某个列,再根据统计值变换该列内容

my $df = [
  [ 'a', '1' ],
  [ 'b', '2' ],
  [ 'c', '2' ],
];

my $new_df = map_cast_col(
  $df,
  cast_col    => 1,
  map_col_sub => sub {
    my ( $r, $s ) = @_;
    return $r->[1] / $s;
  },
);

print Dumper( $new_df );

#$VAR1 = [
#[ 'a', 1, '0.2' ],
#[ 'b', 2, '0.4' ],
#[ 'c', 2, '0.4' ]
#];

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