for _, row in data.iterrows():
d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
- f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
+ f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
f"duration: "
f"{(int(row['duration']) // 3600):02d}:"
f"{((int(row['duration']) % 3600) // 60):02d}<br>"
for _, row in df.iterrows():
d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
- f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
+ f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
f"<prop> [{row[_UNIT[ttype]]}]: {row[_VALUE[ttype]]:,.0f}<br>"
f"<stdev>"
f"{d_type}-ref: {row['dut_version']}<br>"
for avg, stdev, (_, row) in zip(trend_avg, trend_stdev, df.iterrows()):
d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
- f"date: {row['start_time'].strftime('%d-%m-%Y %H:%M:%S')}<br>"
+ f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
f"trend [pps]: {avg:,.0f}<br>"
f"stdev [pps]: {stdev:,.0f}<br>"
f"{d_type}-ref: {row['dut_version']}<br>"
anomaly_y.append(trend_avg[idx])
anomaly_color.append(_ANOMALY_COLOR[anomaly])
hover_itm = (
- f"date: {x_axis[idx].strftime('%d-%m-%Y %H:%M:%S')}<br>"
+ f"date: {x_axis[idx].strftime('%Y-%m-%d %H:%M:%S')}<br>"
f"trend [pps]: {trend_avg[idx]:,.0f}<br>"
f"classification: {anomaly}"
)