如何用 for 循环 function 替换整列？

Question

input = '18.7m, 17.7m, 11.1m, 9.3m, 6.9m, 9.9m, 4.4m, 1.8m, 7.9m'

multipliers = {'k': 1e3,
               'm': 1e6,
              }

pattern = r'([0-9.]+)([km])'
for number, suffix in re.findall(pattern, input):
    number = float(number)
    print(number * multipliers[suffix])
    
for views in df_tiktok: #THIS IS WHERE I GET STUCK

我想将此 for 循环应用到包含“18.7M、17.7M 和 645.1k”等变量的几列。 基本上，我想将上述 for 循环应用于这些列。

平均观看次数	喜欢平均	评论平均。	股票平均
3个	1870万	2.6M	54.7K
6个	1770万	2.3M	18K

第一次尝试：

likes_avg = [[likes] for likes in tiktok_data]
if 'K' in likes :
        like=likes.strip('K')
        like=float(like)*1000
        likes_avg.append(round(like))
if 'M' in likes :
        like=likes.strip('M')
        like=float(like)*1000000
        likes_avg.append(round(like))

第二次尝试：

input = '18.7m, 17.7m, 11.1m, 9.3m, 6.9m, 9.9m, 4.4m, 1.8m, 7.9m'

multipliers = {'k': 1e3,
               'm': 1e6,
              }

pattern = r'([0-9.]+)([km])'
for number, suffix in re.findall(pattern, input):
    number = float(number)
    print(number * multipliers[suffix])

Answer 1

您可以通过创建一个 function 来简化它

def modify(input):
    if isinstance(input, int) or isinstance(input,float)  :
        return input
    if 'K' in input:
      return  float(input.replace('K',''))*1000
    elif 'M' in input:
      return  float(input.replace('M',''))*1000000
    else:
        return input

然后在 df 的每一列上应用此修改 function

for c in df.columns:
    df[c]= df[c].apply(lambda x: modify(x))

这是我测试后得到的

for c in df.columns:
  df[c] = df[c].apply(lambda x: modify(x))
    

Output

    Views avg.   Likes avg  Comments avg.  Shares avg
0               3  18700000.0      2600000.0     54700.0
1               6  17700000.0      2300000.0     18000.0

或者您可以对整个 df 使用 applymap

df.applymap(lambda x: modify(x))
Out[259]: 
       Views avg.   Likes avg  Comments avg.  Shares avg
0               3  18700000.0      2600000.0     54700.0
1               6  17700000.0      2300000.0     18000.0