如何编写代码合并Pandas DataFrame中值总和≤5的坐标区间？

Here's a practical implementation that aligns with your requirements. The approach iterates through the intervals, accumulating values until adding the next would exceed 5 (or keeping any interval with a value over 5 as a standalone entry).

Code Implementation #

import pandas as pd

# Create the input DataFrame
From = [10, 20, 30, 40, 50, 60, 70]
to = [20, 30, 40, 50, 60, 70, 80]
value = [2, 3, 5, 6, 1, 3, 1]
df = pd.DataFrame({'from': From, 'to': to, 'value': value})

# Initialize variables to track merged intervals
merged_intervals = []
current_start = None
current_end = None
current_sum = 0

# Iterate through each row to build merged intervals
for _, row in df.iterrows():
    current_val = row['value']
    
    # Case 1: Current interval's value exceeds 5, keep it separate
    if current_val > 5:
        # Add any ongoing merged interval first if exists
        if current_sum > 0:
            merged_intervals.append({
                'from': current_start,
                'to': current_end,
                'value': current_sum
            })
            # Reset tracking variables
            current_start = None
            current_end = None
            current_sum = 0
        
        # Add the over-5 interval as a standalone entry
        merged_intervals.append({
            'from': row['from'],
            'to': row['to'],
            'value': current_val
        })
    
    # Case 2: Current value is within limit, check if we can merge it
    else:
        if current_sum + current_val > 5:
            # Can't merge, finalize the current merged interval
            merged_intervals.append({
                'from': current_start,
                'to': current_end,
                'value': current_sum
            })
            # Start a new merged interval with the current row
            current_start = row['from']
            current_end = row['to']
            current_sum = current_val
        else:
            # Start or continue the merged interval
            if current_sum == 0:
                current_start = row['from']
                current_end = row['to']
            else:
                current_end = row['to']  # Update end to current row's to
            current_sum += current_val

# Add any remaining merged interval after loop ends
if current_sum > 0:
    merged_intervals.append({
        'from': current_start,
        'to': current_end,
        'value': current_sum
    })

# Convert the merged list to a DataFrame
result_df = pd.DataFrame(merged_intervals)
print(result_df)

Output #

from  to  value
0    10  30      5
1    30  40      5
2    40  50      6
3    50  80      5

Explanation #

• Tracking Merged Intervals: We use current_start, current_end, and current_sum to keep tabs on the ongoing merged interval as we iterate.
• Over-5 Values: Any interval with a value greater than 5 is immediately added as a standalone entry, and any in-progress merge is finalized first to avoid gaps.
• Merge Logic: For values ≤5, we check if adding the current value to the accumulated sum stays within the 5 limit. If not, we wrap up the current merge and start a new one. If yes, we extend the current merged interval to include the row's end coordinate.
• Final Cleanup: After the loop finishes, we add any remaining merged interval that wasn't finalized during iteration.

内容的提问来源于stack exchange，提问作者The Oracle