Python技术求助：使用values_index列表作为位置索引提取converted列表对应元素的指定区间内容

Hey there! Let's work through how to solve your problem of extracting subsets from your converted list using the indices in values_index.

First, let's recap your core requirement:

• You have converted: a list where each element is a pandas Series (extracted from Excel columns)
• You have values_index: a list of integers, where the i-th value is the starting index for the i-th element in converted
• You need to extract, for each pair, the portion of the Series starting at the given index and going to the end

Implementation Code #

Your existing code already correctly generates values_index and converted, so we just need to add the extraction logic. Here are two straightforward approaches:

Approach 1: List Comprehension (Concise & Efficient)

This is the cleanest way to map each index to its corresponding Series subset:

# Extract subsets using paired indices and Series
extracted_results = [series.iloc[idx:] for series, idx in zip(converted, values_index)]

# Print to verify the results
for idx, subset in enumerate(extracted_results):
    print(f"Subset {idx+1}:\n{subset}\n")

Approach 2: For Loop (More Intuitive for Debugging)

If you prefer a step-by-step loop for easier troubleshooting:

extracted_results = []
for i in range(len(converted)):
    current_series = converted[i]
    start_index = values_index[i]
    # Slice from start_index to the end of the Series
    subset = current_series.iloc[start_index:]
    extracted_results.append(subset)

# Print the results
for idx, subset in enumerate(extracted_results):
    print(f"Subset {idx+1}:\n{subset}\n")

Key Notes #

• zip(converted, values_index) pairs each Series in converted with its matching starting index from values_index
• iloc[idx:] is pandas syntax for slicing a Series: it takes all elements from position idx to the end
• Based on your output, your values_index values (like 40, 62) are all valid for their corresponding Series lengths (66, 103, etc.), so you won't hit index errors here

Full Integrated Code #

Add the extraction logic to the end of your existing code like this:

import os
import pandas as pd
import numpy as np

# Replace with your actual file path
path = "./"  
filelist = os.listdir(path)
filelist = sorted(filelist, key=lambda x: int(os.path.splitext(x)[0]))
print(filelist)

asps = []
for file in filelist:
    if file.endswith('.xlsx'):
        df = pd.read_excel(file)
        asps.append(df)
print(asps)

speed = []
average = []
for table in asps:
    speed.append(table['Reversal Intensities'].iloc[15:25])
print(speed)

for each in speed:
    average.append(np.mean(each))
print(average)

rev_ind = []
for each in asps:
    rev_ind.append(each['Reversal Indices'].iloc[15:25])
print(rev_ind)

c = []
for every in rev_ind:
    b = int(min(every))
    c.append(b)
print(c)

values_index = c
converted = []
for values in asps:
    converted.append(values['conv'].iloc[0:-1])
print(converted)

# --------------------------
# New extraction logic here
# --------------------------
extracted_results = [series.iloc[idx:] for series, idx in zip(converted, values_index)]

print("\n=== Extracted Subsets ===")
for i, res in enumerate(extracted_results):
    print(f"\nSubset {i+1}:")
    print(res)

This will give you exactly the subsets you need from each element in converted.

内容的提问来源于stack exchange，提问作者Mik