所以我试图估算一个DataFrame的列,但出现此错误。
(这是对一个特定列的估算)
function downloadAsFile( canvas, imagename, mime ) {
mime = mime || 'image/png';
imagename = imagename || 'canvasImage.png';
canvas.toBlob( blob => {
if ( window.navigator.msSaveBlob ) { // IE and Edge
window.navigator.msSaveBlob( blob, imagename );
}
else { // Chrome, Firefox. Not tested: Safari
const url = window.URL.createObjectURL( blob );
const a = document.createElement( 'a' );
document.body.appendChild( a );
a.href = url;
a.download = imagename;
a.setAttribute( 'style', 'display:none;' );
a.click();
setTimeout( () => {
window.URL.revokeObjectURL( url );
document.body.removeChild( a );
}, 2000);
}
}, mime );
}
但是我得到这个错误:
from missingpy import MissForest
imputer = MissForest()
Imputed_Pollutants = imputer.fit_transform(df4.Ammonia)
当我尝试重塑它时:
Expected 2D array, got 1D array instead
我仍然遇到错误:
r = df4.Ammonia.reshape(-1,1)
Imputed_Pollutants = imputer.fit_transform(r)
这就是r的样子:
One or more columns have all rows missing
这是 氨气 列在重塑之前的样子:
r:
array([[nan],
[nan],
[nan],
...,
[nan],
[nan],
[nan]])
任何建议都将不胜感激,谢谢大家。
答案 0 :(得分:0)
您的候选列是氨,您要输入缺失值的列。 missingpy库的MissForest()使用其余所有列来实现。更多https://pypi.org/project/missingpy/ 所以试试这个:
from missingpy import MissForest
imputer = MissForest()
Imputed_Pollutants = imputer.fit_transform(df4)
Imputed_Pollutants = pd.DataFrame(Imputed_Pollutants, columns=df4.columns)