The given charts illustrate the proportion of a train company’s performance that were either running late or cancelled in October and November in a single year.
Overall, it can be clearly seen that both charts witnessed considerable fluctuations over the period shown. The percentage of trains running late reached a peak at week 2-November. Meanwhile, the highest proportion of trains cancelled were on week 2-October.
Looking at the data of trains delayed in more detail, 20% of the trains were delayed at week 1-October, before rising significantly to 30% next week. This figure dropped sharply to approximately 5% at week 4-October. Subsequently, the ratio of trains running late jumped dramatically to around 55% at week 2-November which reached a peak over the period. However, it fell significantly at 40% in the following week.
Turning to the information of trains cancelled, the proportion of trains cancelled stood at only 1%. Surprisingly, this figure increased dramatically 7 times on week 2-October before falling again to 1% (initial figure) on week 3-October. In the last week of October, trains cancelled rose slightly to 3% then dropping back to 1% in the first week of November. Lastly, this fluctuation appeared again and stopped at 4% on week 3-November.