如何将数据帧中对象列中的“k”或“m”替换为000s,并替换非数字值?

str.translate str.replace

df['col1'] = df.col1.str.translate(str.maketrans({'k':'000','m':'000000'}))
>>> df
               col1
0               100
1            100000
2  100000-100000000
3          10000000
4                50

# df['col1'] = pd.to_numeric(df.col1.str.translate(str.maketrans({'k':'000','m':'000000'})),errors='coerce')

#          col1
# 0       100.0
# 1    100000.0
# 2         NaN
# 3  10000000.0
# 4        50.0

创建映射字典并使用 str.replace :

dct = {'k': '000', 'm': '000000'}

df.col1.str.replace(r'|'.join(dct.keys()), lambda x: dct[x.group()])

0                 100
1              100000
2    100000-100000000
3            10000000
4                  50
Name: col1, dtype: object

如果要删除第三行而不是替换,如在输出中:

(pd.to_numeric(df.col1.str.replace(r'|'.join(dct.keys()),
    lambda x: dct[x.group()]), errors='coerce'))

0         100.0
1      100000.0
2           NaN
3    10000000.0
4          50.0
Name: col1, dtype: float64

import pandas as pd

df = pd.Series(['100','100k','100k-100m','10m','50'])

df = df.str.replace('k', '000', regex=True)
df = df.str.replace('m', '000000', regex=True)
df = pd.to_numeric(df, errors='coerce')
df = df.apply(str).str.split('.', expand=True).iloc[ : , 0 ]

print(df)