pandas read_csv 嘗試讀取 csv 時失敗

Question

所以當我試圖閱讀印度尼西亞出生時的預期壽命時（ https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=ID如果您想查看，這是鏈接）我可以`t，這是我的代碼

import pandas as pd
import matplotlib.pyplot as plt

lifeexpectacion = pd.read_csv("API_SP.DYN.LE00.IN_DS2_en_csv_v2_4770434.csv")
print(lifeexpectacion)

錯誤是

 File "D:\programaizar\data economy\main.py", line 4, in <module>
lifeexpectacion = pd.read_csv("API_SP.DYN.LE00.IN_DS2_en_csv_v2_4770434.csv")

Answer 1

CSV 的前 4 行包含標題、上次更新日期等信息。您需要跳過數據文件的前 4 行。 使用pd.read_csv("API_SP.DYN.LE00.IN_DS2_en_csv_v2_4770434.csv", skiprows=4)

Answer 2

我下載了鏈接文件，看看是否可以重現錯誤。 這篇文章有類似的問題。

csv 的前四行是：

"Data Source","World Development Indicators",

"Last Updated Date","2022-12-22",

如果刪除這些行，它會按預期工作。 元數據讓 pandas 誤以為只有兩列，而實際上是六十七列。

Answer 3

為我工作

df = pd.read_csv(r'D:\temp\API_SP.DYN.LE00.IN_DS2_en_csv_v2_4770434.csv',skiprows=4)
    df
    Out[149]: 
                        Country Name Country Code  ... 2021 Unnamed: 66
    0                          Aruba          ABW  ...  NaN         NaN
    1    Africa Eastern and Southern          AFE  ...  NaN         NaN
    2                    Afghanistan          AFG  ...  NaN         NaN
    3     Africa Western and Central          AFW  ...  NaN         NaN
    4                         Angola          AGO  ...  NaN         NaN
    ..                           ...          ...  ...  ...         ...
    261                       Kosovo          XKX  ...  NaN         NaN
    262                  Yemen, Rep.          YEM  ...  NaN         NaN
    263                 South Africa          ZAF  ...  NaN         NaN
    264                       Zambia          ZMB  ...  NaN         NaN
    265                     Zimbabwe          ZWE  ...  NaN         NaN
    [266 rows x 67 columns]

df.columns
Out[150]: 
Index(['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code',
       '1960', '1961', '1962', '1963', '1964', '1965', '1966', '1967', '1968',
       '1969', '1970', '1971', '1972', '1973', '1974', '1975', '1976', '1977',
       '1978', '1979', '1980', '1981', '1982', '1983', '1984', '1985', '1986',
       '1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995',
       '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004',
       '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013',
       '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021',
       'Unnamed: 66'],
      dtype='object')