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import pymannkendall as mk

columns = [pd.Grouper(key='date', freq='1M'),"category"]
df_tmp = df.groupby(columns)["id"].count().reset_index()
df_tmp = df_tmp.pivot(index='date', columns="category", values="id")

df_tmp.head()

for c in df_tmp.columns:
    print(c, mk.original_test(df_tmp[c]))

Taxes Mann_Kendall_Test(trend='no trend', h=False, p=0.4537606536684353, z=-0.7491602012882456, Tau=-0.07729468599033816, s=-80.0, var_s=11120.0, slope=-0.07692307692307693, intercept=12.73076923076923)
Election Mann_Kendall_Test(trend='increasing', h=True, p=5.887437204421531e-10, z=6.19341519883772, Tau=0.6113945578231292, s=719.0, var_s=13439.666666666666, slope=1.2307692307692308, intercept=-15.53846153846154)
Miscellaneous Mann_Kendall_Test(trend='increasing', h=True, p=7.39592225018626e-07, z=4.950667889212743, Tau=0.48894557823129253, s=575.0, var_s=13443.0, slope=1.6, intercept=5.599999999999994)
Jobs Mann_Kendall_Test(trend='no trend', h=False, p=0.06007191105409859, z=1.8802654388053852, Tau=0.18622448979591838, s=219.0, var_s=13442.333333333334, slope=0.45993589743589747, intercept=16.96153846153846)
Foreign policy Mann_Kendall_Test(trend='increasing', h=True, p=4.468484731567912e-06, z=4.588310126750996, Tau=0.4532312925170068, s=533.0, var_s=13443.666666666666, slope=1.7655677655677655, intercept=5.626373626373628)
Health care Mann_Kendall_Test(trend='increasing', h=True, p=0.003830392987950404, z=2.891801969172867, Tau=0.2857142857142857, s=336.0, var_s=13420.0, slope=0.6, intercept=8.600000000000001)
Economy Mann_Kendall_Test(trend='increasing', h=True, p=7.5848869081074355e-06, z=4.47657826924699, Tau=0.4421768707482993, s=520.0, var_s=13441.333333333334, slope=1.5, intercept=13.0)
Crime Mann_Kendall_Test(trend='increasing', h=True, p=0.005129403454570802, z=2.7987928379985254, Tau=0.30365853658536585, s=249.0, var_s=7851.666666666667, slope=0.3114224137931034, intercept=0.7715517241379315)
Biographical record Mann_Kendall_Test(trend='increasing', h=True, p=2.537511160594086e-05, z=4.211437186129184, Tau=0.41581632653061223, s=489.0, var_s=13427.0, slope=0.5669642857142857, intercept=1.3928571428571423)
Trade Mann_Kendall_Test(trend='increasing', h=True, p=0.0015476267343075278, z=3.1656014682783176, Tau=0.31648936170212766, s=357.0, var_s=12647.0, slope=1.4, intercept=13.100000000000001)
Coronavirus Mann_Kendall_Test(trend='no trend', h=False, p=0.854777098065548, z=0.1830266628259689, Tau=0.05128205128205128, s=4.0, var_s=268.6666666666667, slope=1.9, intercept=173.6)
Environment Mann_Kendall_Test(trend='increasing', h=True, p=0.00011357394008193467, z=3.85959749271286, Tau=0.39420289855072466, s=408.0, var_s=11120.0, slope=0.6774193548387096, intercept=-3.241935483870966)
Immigration Mann_Kendall_Test(trend='increasing', h=True, p=0.0031830744550183088, z=2.949481678500662, Tau=0.2916666666666667, s=343.0, var_s=13445.0, slope=1.0544117647058824, intercept=24.694117647058825)
Ukraine probe Mann_Kendall_Test(trend='no trend', h=False, p=0.5803233039560811, z=-0.5529125344970479, Tau=-0.09473684210526316, s=-18.0, var_s=945.3333333333334, slope=-1.4807692307692308, intercept=34.06730769230769)
Education Mann_Kendall_Test(trend='increasing', h=True, p=0.0004247491629332245, z=3.524208946884208, Tau=0.5368421052631579, s=102.0, var_s=821.3333333333334, slope=0.5608974358974359, intercept=-3.8285256410256414)
Russia Mann_Kendall_Test(trend='increasing', h=True, p=0.0021968586167722126, z=3.0622418689825937, Tau=0.30272108843537415, s=356.0, var_s=13439.333333333334, slope=0.8473193473193473, intercept=13.664335664335663)
Guns Mann_Kendall_Test(trend='no trend', h=False, p=0.08085326476209298, z=1.7457565456730801, Tau=0.2275132275132275, s=86.0, var_s=2370.6666666666665, slope=0.05718954248366013, intercept=1.2279411764705883)
Terrorism Mann_Kendall_Test(trend='no trend', h=False, p=0.6234763980218079, z=-0.49092937766616757, Tau=-0.06884057971014493, s=-19.0, var_s=1344.3333333333333, slope=0.0, intercept=1.0)