Question

我有2个数据框；

import pandas as pd

data1 = {"name": ["a","b","c","d","e"], "value": [0.01,0.02,0.03,0.04,0.05]}

df1 = pd.DataFrame (data1, columns = ['name', 'value'])

data2 = {"value": [0.01,0.03,0.05]}

df2 = pd.DataFrame (data2, columns = ['value'])

我想使用df2中的值来查找df1中对应的名称，并将其添加为新列。即以这个df结尾：

data3 = {"value": [0.01,0.03,0.05], "name": ["a","c","e"]}

df3 = pd.DataFrame (data3, columns = ['value', 'name'])

Answer 1

您在这里：

$matrix = [
      [
        [3, 5, 13, 56],
        [0, 1, 165, 1],
        [-8, 78, 5, 8],
        [6, 5, 23, 45]
    ],
    [
        [1, 17, 5, 3],
        [1, 5, 1, 65],
        [6, 5, 5, -4],
        [0, 4, 3, 90]
    ],
    [
        [9, 9, 8, 0],
        [3, 5, 4, 8],
        [0, 5, 3, 9],
        [1, 4, 5, 7]
    ]
];
function color(&$matrix){
    for ($i = 0; $i < count($matrix); ++$i) {
        echo 'layer ' . ($i + 1) . ':' . PHP_EOL;
        foreach ($matrix as $j) {
            if($i == 1){
                $y=0;
                foreach ($j as $k) {
                    if($y == 0 )
                            echo   $f = 1 . ' ';
                    elseif($y == 1)
                            echo   $f = 0 . ' ';
                    elseif($y == 2)  
                            echo   $f = 1 . ' ';         
                    $y++;   
                }
            }else{
                foreach ($j as $k) {
                    echo $k = 1 . ' ';
                }  
            }
            echo PHP_EOL;
        }
    }
}

输出：

print(df2.merge(df1, on='value'))

Answer 2

您可以在此处pd.Series.isin中使用boolean indexing并将其用作遮罩。

df1[df1['value'].isin(df2['value'])]

  name  value
0    a   0.01
2    c   0.03
4    e   0.05

使用df列中的值从另一个df中查找名称

2 个答案: