can somebody help me to correct my following code at the styling point in Pandas Python

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for idx,ids in enumerate(uniq):
    SV = df_CenteredWin[df_CenteredWin['subVoyageIDs'] == ids]

    SV['minGroup']= np.isnan(SV.groupby(pd.TimeGrouper('30T')).DateTime.diff().dt.seconds)
    SV['groups'] = (SV['minGroup'].shift(1) != SV['minGroup']).astype(int).cumsum()
    SV_Noise = SV[SV['zScore_Noise'] == 'noise']
    uniqueID= SV_Noise.groups.unique()

    print(uniqueID, SV_Noise.subVoyageIDs.unique())

    for idx, groupid in enumerate(uniqueID):
        groups = SV[SV['groups'] == groupid]
        groups_nosie = groups[groups['zScore_Noise'] == 'noise']
        data = pd.DataFrame(data = { 'distance' : groups.Distance,
                       'Speed' : groups.Speed,
                        'Z-Score' :  groups.centeredZScore,
                         'flagged' :  groups.zScore_Noise.values})
        display(data.style.apply(lambda x: ['background: Yellow' if x.name == 'noise' else data for i in x]))

can anyone explain me what is wrong in this line, and how can I correct it

display(data.style.apply(lambda x: ['background: Yellow' if x.name == 'noise' else data for i in x]))

I have this following data where i am trying to highlight the row where the flagged column is equal to 'noise'

 DateTime            Speed      Score        Distance   flagged
2011-01-09 12:21:59 1.840407   -0.845713    0.030673    noisefree
2011-01-09 12:23:00 4.883493    2.307917    0.082748    noisefree
2011-01-09 12:24:00 4.413968    1.752545    0.073566    noisefree
2011-01-09 12:24:59 4.950600    2.178342    0.081135    noisefree
2011-01-09 12:26:00 10.014879   4.355568    0.169697    noise
2011-01-09 12:27:00 7.534325    2.535460    0.125572    noisefree
2011-01-09 12:27:59 6.965328    2.122056    0.114154    noisefree
2011-01-09 12:29:00 6.993480    1.963185    0.118501    noisefree

and the error is: 

AttributeError: 'DataFrame' object has no attribute 'rstrip'
python-3.6 pandas styles python
1 Answers

You were close. I'm not exactly sure why you got THAT error, but one issue was that you were returning your initial dataframe within the else block of your list comprehension.

If you replace that line with this, you may have better luck.

df.style.apply(lambda x: ["background: yellow" if v == "noise" else "" for v in x], axis = 1)

In this case, you are iterating over each row in your df, highlighting cells that equal noise.

Help from / possible duplicate of Conditionally format Python pandas cell

Edit: Ripping off @scott-boston and How to use Python Pandas Stylers for coloring an entire row based on a given column?,

def highlight_row(s,keyword,column):
    is_keyword = pd.Series(data=False, index=s.index)
    is_keyword[column] = s.loc[column] == keyword
    return ['background-color: yellow' if is_keyword.any() else '' for v in is_keyword]

df.style.apply(highlight_row, keyword="noise", column=["flagged"], axis=1)
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