使用库替换 python 中的列值
using library to replace column values in python
我正在尝试使用我们的库将 FIPS 代码替换为州缩写。这就是我如何获得每个州的价值
fips_name = us.states.mapping('fips', 'name')
fips_name['20']
Out[31]: 'Kansas'
假定 fips_name
是 fips -> state names
的字典,您可以使用 pandas.Series
(列)的 .map
方法:
df["state_names"] = df["fips"].map(fips_name)
更新工作示例:
import pandas as pd
import us
df = pd.DataFrame({"fips": ["01", "01", "08", "09", "10", "06"]})
fips_to_name = us.states.mapping("fips", "name")
df["states"] = df["fips"].map(fips_to_name)
print(df)
fips states
0 01 Alabama
1 01 Alabama
2 08 Colorado
3 09 Connecticut
4 10 Delaware
5 06 California
我正在尝试使用我们的库将 FIPS 代码替换为州缩写。这就是我如何获得每个州的价值
fips_name = us.states.mapping('fips', 'name')
fips_name['20']
Out[31]: 'Kansas'
假定 fips_name
是 fips -> state names
的字典,您可以使用 pandas.Series
(列)的 .map
方法:
df["state_names"] = df["fips"].map(fips_name)
更新工作示例:
import pandas as pd
import us
df = pd.DataFrame({"fips": ["01", "01", "08", "09", "10", "06"]})
fips_to_name = us.states.mapping("fips", "name")
df["states"] = df["fips"].map(fips_to_name)
print(df)
fips states
0 01 Alabama
1 01 Alabama
2 08 Colorado
3 09 Connecticut
4 10 Delaware
5 06 California