如何将Pandas中的对象值转换为字符串值？

Question

我在把这些列里的值变成字符串类型时遇到了问题：['Product', 'Product subtype/Category/Commodity', 'Mode of transportation', 'Origin', 'Destination', 'Port', 'Activity', 'Units']

import pandas as pd
import matplotlib.pyplot as plt
import requests

url = r'https://www.neb-one.gc.ca/open/imports-exports/imports-exports-data-visualization.csv'
df = pd.read_csv(url,encoding='ISO-8859-1')

# Filtering out specific transactional activities and confidential values
clean = (~df.iloc[:,7].isin(['Export / Re-imports' ,'Import / Re-exports','Re-export / Imports' ,'Re-import / Exports']))&(df.iloc[:,-1]!="Confidential")
dfIE = df[clean].copy()



dfIE[['Year','Quarter']] = dfIE['Period'].str.split('Q', expand = True)
dfIE.drop(columns=['Period'], inplace=True)
dfIE.insert(0, 'Year', dfIE.pop('Year'))
dfIE.insert(1, 'Quarter', dfIE.pop('Quarter'))

dfIE['Value'] = pd.to_numeric(dfIE['Value'], errors='coerce')
dfIE['Year'] = pd.to_numeric(dfIE['Year'], errors='coerce')
dfIE['Quarter'] = pd.to_numeric(dfIE['Quarter'], errors='coerce')

我尝试了下面三种方法来把对象的值转换成字符串。

注意：有些值是'NaN'，表示不是一个数字。

column_name =[ 'Product', 'Product subtype/Category/Commodity', 'Mode of transportation', 'Origin', 'Destination', 'Port', 'Activity', 'Units']
dfIE[column_name]= dfIE[column_name].astype(str)
dfIE[column_name]= dfIE[column_name].values.astype(str)
dfIE[column_name]= dfIE[column_name].map(str)

Answer 1

你需要用 .astype('string') 而不是 .astype(str)。想了解更多，可以点击 这里。

column_name =['Product', 'Product subtype/Category/Commodity', 'Mode of transportation', 'Origin', 'Destination', 'Port', 'Activity', 'Units']
dfIE[column_name]= dfIE[column_name].astype('string')

df.info():

<class 'pandas.core.frame.DataFrame'>
Index: 48582 entries, 0 to 54028
Data columns (total 11 columns):
 #   Column                              Non-Null Count  Dtype  
---  ------                              --------------  -----  
 0   Year                                48582 non-null  int64  
 1   Quarter                             48582 non-null  int64  
 2   Product                             48582 non-null  string 
 3   Product subtype/Category/Commodity  22682 non-null  string 
 4   Mode of transportation              299 non-null    string 
 5   Origin                              19403 non-null  string 
 6   Destination                         41902 non-null  string 
 7   Port                                5560 non-null   string 
 8   Activity                            48582 non-null  string 
 9   Units                               48582 non-null  string 
 10  Value                               37806 non-null  float64
dtypes: float64(1), int64(2), string(8)
memory usage: 4.4 MB