API输出转DataFrame最简方法及ACLED数据读取空表问题排查

Hey there! Let's break down your questions and fix that ACLED API issue step by step.

The simplest approach depends on what format the API returns:

• If the API returns a JSON array (directly a list of records):
  Just pass the parsed JSON directly to pd.DataFrame():

  import pandas as pd
  import requests
  
  response = requests.get("your_api_url")
  df = pd.DataFrame(response.json())
  

• If the API returns a nested JSON (with a data field holding the records):
  Extract the specific key (usually data) that contains the dataset array first:

  df = pd.DataFrame(response.json()['data'])
  

• If the API supports CSV output:
  Skip the JSON parsing entirely and use pd.read_csv() directly with the API URL that returns CSV.

Your original code fails because you're using pd.read_csv() to read a JSON response. Let's look at why and fix it:

What went wrong? #

The URL you used appended .csv to the end, but the ACLED API is still returning a JSON structure (as shown in your output). The CSV parser can't interpret this JSON as valid CSV, so it treats the entire JSON string as a single column name with no data rows—hence the empty DataFrame.

Fixed Code #

Use requests to fetch the JSON data, extract the data array from the response, then convert it to a DataFrame:

import requests
import pandas as pd

# Fetch the JSON data from ACLED API
url = "https://api.acleddata.com/acled/read?terms=accept&country=Afghanistan&date=20200315"
response = requests.get(url)

# Ensure the request succeeded
response.raise_for_status()

# Parse JSON and convert the 'data' array to DataFrame
acled_data = response.json()
AcledData = pd.DataFrame(acled_data['data'])

# Check the result
print(AcledData.head())

This will correctly load the event records into a DataFrame with proper columns and rows.

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