Select, sort and derive columns without losing alignment

A mask selects rows; sorting changes their order; a derived column must still line up with those selected observations. Pandas aligns Series by index labels, which is useful when intentional and surprising when a fresh default-index Series is assigned to a frame with old labels.

The exercise selects known cents above a threshold, sorts with a stable tie policy and formats currency using integer arithmetic. It preserves the source index as evidence of which observations remain. It does not reset labels and pretend the row positions are the original identities.

Nullable comparisons can produce pd.NA. Combine the nonmissing check with the comparison and fill an unknown mask value with False. Do not rely on Python truthiness to select data with nullable scalars.

Sort descending cents, then ascending sale_id. Use a stable sort policy and preserve original labels. Assign derived text using a positional Pandas array so index alignment cannot put an otherwise correct amount on the wrong row.

import pandas as pd
frame=pd.DataFrame({"id":["b","a","c"],"cents":pd.array([29,29,None],dtype="Int64")},index=[10,20,30])
mask=frame["cents"].notna() & frame["cents"].ge(0).fillna(False)
result=frame.loc[mask].sort_values(["cents","id"],ascending=[False,True],kind="stable")
print(result["id"].tolist(),result.index.tolist())

The derived label uses sign, absolute integer cents, whole units and a two-digit remainder. It preserves zero and refunds without binary float conversion. The result is a new frame, while the input retains its columns, values and index.

Read the index as labels when using loc. Use iloc for positional inspection. Reset an index only when that is an intentional new convention; do not confuse resetting labels with repairing a broken alignment.

for cents in (0,29,-125):
    value=abs(cents)
    print(("-" if cents<0 else "")+f"${value//100}.{value%100:02d}")

Implement the mask, tie ordering and integer formatting. Preserve source labels and verify both a refund and an empty result. Next retain why an amount is absent.