迭代行和应用转换的有效方法

Efficient Way to Iterate Through Rows and Apply Conversions

我正在寻找一种更有效的方法来执行检查,然后在必要时应用转换。

这是我当前的代码

for i in tqdm(df.index):
    if df.loc[i,'WHP Total Acres'] > df.loc[i,'GIS_ACRES']:
        conv_factor = (df.loc[i,'GIS_ACRES'])/(df.loc[i,'WHP Total Acres'])
        df.loc[i,'Very Low'] = df.loc[i,'Very Low'] * conv_factor
        df.loc[i,'Low'] = df.loc[i,'Low'] * conv_factor
        df.loc[i,'Moderate'] = df.loc[i,'Moderate'] * conv_factor
        df.loc[i,'High'] = df.loc[i,'High'] * conv_factor
        df.loc[i,'Very High'] = df.loc[i,'Very High'] * conv_factor
    else:
        df.loc[i, 'WHP Total Acres'] = df.loc[i,'WHP Total Acres']

要遍历 350K 条记录,这在我的机器上大约需要 2 个小时。我相信一定有更有效的方法。

df['conv_factor'] = 1
df.loc[df['WHP Total Acres'] > df['GIS_ACRES'],'conv_factor'] = df['GIS_ACRES']/df['WHP Total Acres']

df['Very Low'] = df['conv_factor'] * df['Very Low']
.
.
.

conv_factor 创建一个辅助列,然后相乘应该得到结果。

只需使用 loc 即可更改所需的值。