如何将 x 年 y 月的列转换为 [12(x)+y] 个月

发布于 2025-01-16 21:41:46 字数 695 浏览 0 评论 0原文

我的数据有一个剩余租赁列，该列位于 x 年 y 个月内我想将其更改为 [12(x)+y] 个月 Here is a picture of the data

我已尝试下面的代码，但不断发生错误

import pandas as pd

def lease_string_to_months(time):
    split_string = time.split(' ')
    months = 12*int(split_string[0]) + int(split_string[2])
    return months

df1 = 'resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv' # write the filepath here as a string
house_lease = pd.read_csv(df1)
new_header = house_lease.iloc[0]
house_lease = house_lease[1:]
house_lease.columns = new_header
house_lease['remaining_lease'].map(lease_string_to_months)

原文

My data has a remaining_lease column where it is in x years and y months
I would like to change it into [12(x)+y] months
Here is a picture of the data

I have tried the code below but an error keeps occuring

import pandas as pd

def lease_string_to_months(time):
    split_string = time.split(' ')
    months = 12*int(split_string[0]) + int(split_string[2])
    return months

df1 = 'resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv' # write the filepath here as a string
house_lease = pd.read_csv(df1)
new_header = house_lease.iloc[0]
house_lease = house_lease[1:]
house_lease.columns = new_header
house_lease['remaining_lease'].map(lease_string_to_months)

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許願樹丅啲祈禱 2025-01-23 21:41:46

首先 - 阅读 pd.read_csv() 以及检查 house_lease 中的内容。换句话说，我怀疑你是否需要大部分转变。

由于我没有您的 cvs 文件，因此我在这里制作了一个玩具示例，拆分 remaining_lease （字符串）列，转换为第 [0] 列和第 [0] 列。第 2 列编号，将 12*Y+M 推送到数据框中新的 months 列。

import pandas as pd
d = {'remaining_lease': ['55 years 12 months', '12 years 01 months']}
df = pd.DataFrame(d)
rdf = df['remaining_lease'] \
    .str.split(r" ", expand=True) \
    .iloc[:, [0,2]] \
    .apply(pd.to_numeric)
df['months'] = 12*rdf[0] + rdf[2]

print(df)

>     remaining_lease  months
0  55 years 12 months     672
1  12 years 01 months     145

First - read about pd.read_csv() as well as inspect what you have in house_lease. In other words, I doubt that you need most of your transformations.

Since I don't have your cvs file, I made toy example here, split remaining_lease (string) column, converted [0]th & 2th columns to number, pushed 12*Y+M to a new months column in dataframe.

import pandas as pd
d = {'remaining_lease': ['55 years 12 months', '12 years 01 months']}
df = pd.DataFrame(d)
rdf = df['remaining_lease'] \
    .str.split(r" ", expand=True) \
    .iloc[:, [0,2]] \
    .apply(pd.to_numeric)
df['months'] = 12*rdf[0] + rdf[2]

print(df)

>     remaining_lease  months
0  55 years 12 months     672
1  12 years 01 months     145

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