Jupyter Notebook中R转Python遇NameError：hosp_info未定义求助

我是Python新手，在Jupyter Notebook中将R代码转换为Python代码时，持续触发报错，提示NameError: name 'hosp_info' is not defined。以下是相关代码及报错信息，恳请协助排查解决：

原始R代码 #

# Get the unique hospital names
hosp_names = hosp_info %>% 
  filter(`Hospital Type` == "Acute Care Hospitals") %>%
  filter(State == "CA") %>%
  pull(`Hospital Name`)

# Filter based on those hospital names
hosp_info_CA = 
hosp_info %>% 
  rename(Hospital = `Hospital Name`,
         Provider_ID = `Provider ID`,
         Safety = `Safety of care national comparison`,
         Effectiveness = `Effectiveness of care national comparison`
         ) %>%
  filter(Hospital %in% hosp_names, State == "CA") %>%
  mutate(Overall_Rating = as.numeric(`Hospital overall rating`)) %>%
  drop_na(Overall_Rating)

hosp_info_CA %>% 
  arrange(desc(Overall_Rating), Hospital) %>% 
  head(7)

hosp_info_CA %>% 
  group_by(Overall_Rating, Safety) %>% 
  count()

write_csv(hosp_info_CA, 'hosp_info_CA.csv')

我编写的Python代码 #

import pandas as pd #import panda

hosp_names = hosp_info
hosp_info = [(hosp_info[" Hospital Type "] == " Acute Care Hospitals ") & (hosp_info[" State "] == " CA ")].loc[:,[" Hospital Name "]].unique()

hosp_info_CA = hosp_info.rename(columns={" Hospital Name ": " Hospital ", " Provider ID ": " Provider_ID ", " Safety of care national comparison ": " Safety ", " Effectiveness of care national comparison ": " Effectiveness "}).loc[hosp_info[" Hospital "].isin(hosp_names) & (hosp_info[" State "] == " CA ")].dropna(subset=[" Hospital overall rating "]).assign(Overall_Rating = lambda x: pd.to_numeric(x[" Hospital overall rating "]))

hosp_info_CA.sort_values(by=" Overall_Rating ", ascending=False).head(7)

hosp_info_CA.groupby([" Overall_Rating ", " Safety "]).count()

hosp_info_CA.to_csv(" hosp_info_CA.csv ")

报错信息 #

NameError                                 Traceback (most recent call last)
 in 
3
4 # Get the unique hospital names
----> 5 hosp_names = hosp_info
6 hosp_info = [(hosp_info[" Hospital Type "] == " Acute Care Hospitals ") & (hosp_info[" State "] == " CA ")].loc[:,[" Hospital Name "]].unique()
7

NameError: name 'hosp_info' is not defined

问题根源及修正方案 #

1. 核心错误：未加载原始数据 #

R代码默认hosp_info已经是读入内存的数据框，但Python里你完全没写读取数据的代码。必须先把你的医院数据文件（比如CSV/Excel）读入成DataFrame，比如：

# 替换成你的实际文件路径
hosp_info = pd.read_csv("your_hospital_data.csv")

2. 代码逻辑错误修正 #

• 删掉第一行无意义的hosp_names = hosp_info，这行不仅没用，还直接触发未定义错误。
• 筛选hosp_names的写法错误：不能把条件放在列表里，要直接对DataFrame做筛选后提取列。
• 列名空格问题：如果原始数据列名确实带前后空格，建议先清理列名，避免后续出错；如果是你手动加的空格，要去掉。
• 拆分链式调用，避免一行代码太复杂，方便调试。

修正后的完整Python代码 #

import pandas as pd

# 第一步：读取原始数据（替换为你的实际文件路径）
hosp_info = pd.read_csv("your_hospital_data.csv")

# 清理列名（可选，但推荐：去掉列名前后空格）
hosp_info.columns = hosp_info.columns.str.strip()

# 获取加州急性护理医院的唯一名称
hosp_names = hosp_info[(hosp_info["Hospital Type"] == "Acute Care Hospitals") & (hosp_info["State"] == "CA")]["Hospital Name"].unique()

# 处理得到hosp_info_CA
hosp_info_CA = (hosp_info
                .rename(columns={
                    "Hospital Name": "Hospital",
                    "Provider ID": "Provider_ID",
                    "Safety of care national comparison": "Safety",
                    "Effectiveness of care national comparison": "Effectiveness"
                })
                .loc[(hosp_info["Hospital Name"].isin(hosp_names)) & (hosp_info["State"] == "CA")]
                .assign(Overall_Rating=lambda x: pd.to_numeric(x["Hospital overall rating"], errors="coerce"))
                .dropna(subset=["Overall_Rating"])
               )

# 查看Top7高评分医院
print(hosp_info_CA.sort_values(by="Overall_Rating", ascending=False).head(7))

# 按评分和安全等级分组计数
print(hosp_info_CA.groupby(["Overall_Rating", "Safety"]).size())

# 保存结果
hosp_info_CA.to_csv("hosp_info_CA.csv", index=False)

内容的提问来源于stack exchange，提问作者ex_lvl_99_warlock