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diff --git a/csit.infra.dash/app/pal/news/tables.py b/csit.infra.dash/app/pal/news/tables.py
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+++ b/csit.infra.dash/app/pal/news/tables.py
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+# Copyright (c) 2022 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""The tables with news.
+"""
+
+import pandas as pd
+import dash_bootstrap_components as dbc
+
+from datetime import datetime, timedelta
+
+
+def _table_info(job_data: pd.DataFrame) -> dbc.Table:
+    """Generates table with info about the job.
+
+    :param job_data: Dataframe with information about the job.
+    :type job_data: pandas.DataFrame
+    :returns: Table with job info.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(
+            {
+                "Job": job_data["job"],
+                "Last Build": job_data["build"],
+                "Date": job_data["start"],
+                "DUT": job_data["dut_type"],
+                "DUT Version": job_data["dut_version"],
+                "Hosts": ", ".join(job_data["hosts"].to_list()[0])
+            }
+        ),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color="info"
+    )
+
+
+def _table_failed(job_data: pd.DataFrame, failed: list) -> dbc.Table:
+    """Generates table with failed tests from the last run of the job.
+
+    :param job_data: Dataframe with information about the job.
+    :param failed: List of failed tests.
+    :type job_data: pandas.DataFrame
+    :type failed: list
+    :returns: Table with fialed tests.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(
+            {
+                (
+                    f"Last Failed Tests on "
+                    f"{job_data['start'].values[0]} ({len(failed)})"
+                ): failed
+            }
+        ),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color="danger"
+    )
+
+
+def _table_gressions(itms: dict, color: str) -> dbc.Table:
+    """Generates table with regressions.
+
+    :param itms: Dictionary with items (regressions or progressions) and their
+        last occurence.
+    :param color: Color of the table.
+    :type regressions: dict
+    :type color: str
+    :returns: The table with regressions.
+    :rtype: dbc.Table
+    """
+    return dbc.Table.from_dataframe(
+        pd.DataFrame.from_dict(itms),
+        bordered=True,
+        striped=True,
+        hover=True,
+        size="sm",
+        color=color
+    )
+
+
+def table_news(data: pd.DataFrame, job: str, period: int) -> list:
+    """Generates the tables with news:
+    1. Falied tests from the last run
+    2. Regressions and progressions calculated from the last C.NEWS_TIME_PERIOD
+       days.
+
+    :param data: Trending data with calculated annomalies to be displayed in the
+        tables.
+    :param job: The job name.
+    :param period: The time period (nr of days from now) taken into account.
+    :type data: pandas.DataFrame
+    :type job: str
+    :type period: int
+    :returns: List of tables.
+    :rtype: list
+    """
+
+    last_day = datetime.utcnow() - timedelta(days=period)
+    r_list = list()
+    job_data = data.loc[(data["job"] == job)]
+    r_list.append(_table_info(job_data))
+
+    failed = job_data["failed"].to_list()[0]
+    if failed:
+        r_list.append(_table_failed(job_data, failed))
+
+    title = f"Regressions in the last {period} days"
+    regressions = {title: list(), "Last Regression": list()}
+    for itm in job_data["regressions"].to_list()[0]:
+        if itm[1] < last_day:
+            break
+        regressions[title].append(itm[0])
+        regressions["Last Regression"].append(
+            itm[1].strftime('%Y-%m-%d %H:%M'))
+    if regressions["Last Regression"]:
+        r_list.append(_table_gressions(regressions, "warning"))
+
+    title = f"Progressions in the last {period} days"
+    progressions = {title: list(), "Last Progression": list()}
+    for itm in job_data["progressions"].to_list()[0]:
+        if itm[1] < last_day:
+            break
+        progressions[title].append(itm[0])
+        progressions["Last Progression"].append(
+            itm[1].strftime('%Y-%m-%d %H:%M'))
+    if progressions["Last Progression"]:
+        r_list.append(_table_gressions(progressions, "success"))
+
+    return r_list
+
+
+def table_summary(data: pd.DataFrame, jobs: list, period: int) -> list:
+    """Generates summary (failed tests, regressions and progressions) from the
+    last week.
+
+    :param data: Trending data with calculated annomalies to be displayed in the
+        tables.
+    :param jobs: List of jobs.
+    :params period: The time period for the summary table.
+    :type data: pandas.DataFrame
+    :type job: str
+    :type period: int
+    :returns: List of tables.
+    :rtype: list
+    """
+
+    return [
+        dbc.Accordion(
+            children=[
+                dbc.AccordionItem(
+                    title=job,
+                    children=table_news(data, job, period)
+                ) for job in jobs
+            ],
+            class_name="gy-2 p-0",
+            start_collapsed=True,
+            always_open=True
+        )
+    ]