Sorting reorders the rows of a pandas DataFrame so that values become easier to inspect, compare, or rank. Use sort_index to order by index values; use sort_values to order by one or more data columns. The original row order often does not affect calculations such as a mean, but it strongly affects how results are displayed and which records appear first. section 6.0 section 6.1
Table 6.1 What you need to know (view table figure)
Compare index-based ordering with column-based ordering before choosing the operation that matches the question. section 6.0
Start with the analytical question. Ordering sales by department, network statistics by subnet, or projections chronologically makes a report readable. Ordering a numeric column can also expose its highest or lowest records. Choose ascending order for small-to-large values and descending order for large-to-small values. section 6.1
Find and compare the longest taxi rides
Load passenger_count, trip_distance, and total_amount, then sort trip_distance in descending order to put the longest rides first. Take the first 20 rows and calculate their average total_amount. Repeat with ascending order and compare the result: the ordering direction determines whether the first 20 rows are the longest or shortest rides. For a more detailed ranking, sort first by passenger_count ascending and then by trip_distance descending, then average the first 50 rides. section 6.1
Sorting composes naturally with aggregation. After grouping survey responses by employment type and calculating mean annual compensation, sort the resulting Series in descending order to make the highest averages immediately visible. Clean display-oriented results afterward by dropping missing values and formatting numbers; sorting itself does not make questionable or missing values disappear. section 8.2
Useful habits when ordering results:
- Sort by index only when the index carries the ordering you need; otherwise sort by named value columns. section 6.0
- Use descending order before head when investigating the largest values, counts, or proportions. section 8.2
- Use multiple sort keys when one field organizes groups and another ranks records within them. section 6.1
- Inspect missing values in ranked summaries, then use dropna when a clean comparison is required. section 8.2
Sorting is a presentation and investigation tool rather than a substitute for analysis. It helps turn grouped means, value counts, pivoted measures, and filtered subsets into ranked outputs that are easier to question. A surprising top result can be a prompt to check missing data, sample composition, or whether the comparison supports the intended claim. section 8.2 section 7.17
