英文:
Pandas:iterate through the dataframe and apply changes with conditions
问题
我必须遍历列= 0，如果我在列= 0中找到任何整数，如2010、2018、2017等，我必须将其分配给列= 0中所有的值作为年份。
我的DF：
0 1
Nan 银行
国家银行 轴银行
Nan ICICI
Nan PNB
2010 KYB
Nan Indus Ind
Nan 卡尔
我的期望输出：
0 1
2010 银行
2010 轴银行
2010 ICICI
2010 PNB
2010 KYB
2010 Indus Ind
2010 卡尔
英文:
I have to iterate through column=0 and if I find any integer like 2010,2018,2017 etc in my column =0, I have to assign that to all the values in column=0 as year.
PS:-column=0 is an object datatype.
My DF:
0 1
Nan Banks
National Banks Axis Bank
Nan ICICI
Nan PNB
2010 KYB
Nan Indus Ind
Nan Karur
My desired output:
0 1
2010 Banks
2010 Axis Bank
2010 ICICI
2010 PNB
2010 KYB
2010 Indus Ind
2010 Karur
答案1
得分: 1
将列转换为数值类型使用 to_numeric，然后使用 Series.where 和 Series.isin 将所有不在 range 范围内的数字转换为缺失值 NaN：
s = pd.to_numeric(df[0], errors='coerce')
df[0] = s.where(s.isin(range(2010, 2020)))
print(df)
0 1
0 NaN Banks
1 NaN Axis Bank
2 NaN ICICI
3 NaN PNB
4 2010.0 KYB
5 NaN Indus Ind
6 NaN Karur
英文:
Convert column to numeric by to_numeric and then convert all numbers outside range to missing values to NaNs by Series.where with mask by Series.isin:
s = pd.to_numeric(df[0], errors='coerce')
df[0] = s.where(s.isin(range(2010, 2020)))
print (df)
0 1
0 NaN Banks
1 NaN Axis Bank
2 NaN ICICI
3 NaN PNB
4 2010.0 KYB
5 NaN Indus Ind
6 NaN Karur
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