I have this data frame df:
I need to style this data frame based on Percent_Utilized column. I have this so far:
I have this data frame:
df
I need to apply style to this data frame based on Percent_Utilized column. I have this solution so far:
df_new [/inline]
this set of code works when there is no empty rows. But there is an empty row in df and I need to keep it to separate each group by env column.
I am currently getting this error:
AttributeError: 'NoneType oject has no attribute 'rstrip'.
Any ideas?
I need to style this data frame based on Percent_Utilized column. I have this so far:
I have this data frame:
df
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Server Env. Model Percent_Utilized server123 Prod Cisco. 50 server567. Prod Cisco. 80 serverabc. Prod IBM. 100 serverdwc. Prod IBM. 45 servercc. Prod Hitachi. 25 Avg 60 server123Uat Uat Cisco. 40 server567u Uat Cisco. 30 serverabcu Uat IBM. 80 serverdwcu Uat IBM. 45 serverccu Uat Hitachi 15 Avg 42 |
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def color(val): if pd.isnull(val): return elif val > 80 : background_color = 'red' elif val > 50 and val < = 80 : background_color = 'yellow' else : background_color = 'green' return 'background-color: %s' % background_color def color_for_avg_row(row): styles = [''] * len (row) if row[ 'Server' ] = = 'Avg' : if row[ 'Percent_Utilized' ] > 80 : color = 'background-color: red' elif row[ 'Percent_Utilized' ] > 50 : color = 'background-color: yellow' else : color = 'background-color: green' styles = [color for _ in row.index] return pd.Series(styles, index = row.index) |
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df_new = (df.style . apply (color_for_avg_row, axis = 1 ) .applymap(color, subset = [ "Percent_Utilized" ])) |
this set of code works when there is no empty rows. But there is an empty row in df and I need to keep it to separate each group by env column.
I am currently getting this error:
AttributeError: 'NoneType oject has no attribute 'rstrip'.
Any ideas?