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Merge pull request#179 from Minku-Koo/osskoo

to update python code for clean code

2 parents9a93481 +bb050f3 commitf126071Copy full SHA for f126071

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python

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`‎python/pandasCommand.py‎`

Lines changed: 3 additions & 4 deletions

Original file line number	Diff line number	Diff line change
`@@ -36,15 +36,14 @@ def _vp_get_columns_list(df):`
`36`	`36`	`cInfo['value']="'{}'".format(c)`
`37`	`37`	`eliftype(c).__name__=='Timestamp':`
`38`	`38`	`cInfo['value']=str(c)`
	`39`	`+`
`39`	`40`	`# category - iopub data rate limit issue...`
	`41`	`+cInfo['category']= []`
`40`	`42`	`ifstr(df[c].dtype)=='object':`
`41`	`43`	`uniqValues=df[c].dropna().unique()`
`42`	`44`	`iflen(uniqValues)<=20:`
`43`	`45`	`cInfo['category']= [{"value":"'{}'".format(u)iftype(u)==strelseu,"label":u }foruinuniqValues]`
`44`		`-else:`
`45`		`-cInfo['category']= []`
`46`		`-else:`
`47`		`-cInfo['category']= []`
	`46`	`+`
`48`	`47`	`colList.append(cInfo)`
`49`	`48`	`returncolList`
`50`	`49`

`‎python/userCommand.py‎`

Lines changed: 13 additions & 3 deletions

Original file line number	Diff line number	Diff line change
`@@ -10,6 +10,7 @@`
`10`	`10`	`importfitz`
`11`	`11`	`importnltk`
`12`	`12`	`nltk.download('punkt')`
	`13`	`+`
`13`	`14`	`######`
`14`	`15`	`# Visual Python: Data Analysis > PDF`
`15`	`16`	`######`
`@@ -43,6 +44,7 @@ def vp_pdf_get_sentence(fname_lst):`
`43`	`44`	`df=_vp_pd.concat([df,df_doc])`
`44`	`45`
`45`	`46`	`returndf.reset_index().drop('index',axis=1)`
	`47`	`+`
`46`	`48`	`######`
`47`	`49`	`# Visual Python: Data Analysis > Frame`
`48`	`50`	`######`
`@@ -63,6 +65,7 @@ def vp_drop_outlier(df, col, weight=1.5):`
`63`	`65`	`df_res=df.drop(outlier_index).copy()`
`64`	`66`
`65`	`67`	`returndf_res`
	`68`	`+`
`66`	`69`	`######`
`67`	`70`	`# Visual Python: Machine Learning > Model Info`
`68`	`71`	`######`
`@@ -74,10 +77,12 @@ def vp_create_feature_importances(model, X_train=None, sort=False):`
`74`	`77`
`75`	`78`	`df_i=_vp_pd.DataFrame(model.feature_importances_,index=feature_names,columns=['Feature_importance'])`
`76`	`79`	`df_i['Percentage']=100* (df_i['Feature_importance']/df_i['Feature_importance'].max())`
`77`		`-ifsort:df_i.sort_values(by='Feature_importance',ascending=False,inplace=True)`
	`80`	`+ifsort:`
	`81`	`+df_i.sort_values(by='Feature_importance',ascending=False,inplace=True)`
`78`	`82`	`df_i=df_i.round(2)`
`79`	`83`
`80`	`84`	`returndf_i`
	`85`	`+`
`81`	`86`	`######`
`82`	`87`	`# Visual Python: Machine Learning > Model Info`
`83`	`88`	`######`
`@@ -91,10 +96,13 @@ def vp_plot_feature_importances(model, X_train=None, sort=False, top_count=0):`
`91`	`96`	`df_i['Percentage'].sort_values().plot(kind='barh')`
`92`	`97`	`else:`
`93`	`98`	`df_i['Percentage'].plot(kind='barh')`
	`99`	`+`
`94`	`100`	`_vp_plt.xlabel('Feature importance Percentage')`
`95`	`101`	`_vp_plt.ylabel('Features')`
`96`		`-`
`97`	`102`	`_vp_plt.show()`
	`103`	`+`
	`104`	`+return`
	`105`	`+`
`98`	`106`	`######`
`99`	`107`	`# Visual Python: Visualization > Seaborn`
`100`	`108`	`######`
`@@ -134,4 +142,6 @@ def _single(ax):`
`134`	`142`	`foridx,axin_vp_np.ndenumerate(axs):`
`135`	`143`	`_single(ax)`
`136`	`144`	`else:`
`137`		`-_single(axs)`
	`145`	`+_single(axs)`
	`146`	`+`
	`147`	`+return`

`‎python/variableCommand.py‎`

Lines changed: 5 additions & 8 deletions

Original file line number	Diff line number	Diff line change
`@@ -1,3 +1,5 @@`
	`1`	`+importnumpyas_vp_np`
	`2`	`+importrandomas_vp_rd`
`1`	`3`	`"""`
`2`	`4`	`Search Variables`
`3`	`5`	`"""`
`@@ -77,8 +79,6 @@ def _vp_get_profiling_list():`
`77`	`79`
`78`	`80`	`returnresult`
`79`	`81`
`80`		`-importnumpyas_vp_np`
`81`		`-importrandomas_vp_rd`
`82`	`82`	`def_vp_sample(data,sample_cnt):`
`83`	`83`	`"""`
`84`	`84`	`Sampling data`
`@@ -94,16 +94,13 @@ def _vp_sample(data, sample_cnt):`
`94`	`94`	`returndata[_vp_np.random.choice(data.shape[0],sample_cnt,replace=False)]`
`95`	`95`	`elifdataType=='list':`
`96`	`96`	`return_vp_rd.choices(data,k=sample_cnt)`
	`97`	`+`
`97`	`98`	`returndata`
`98`	`99`
`99`	`100`	`def_vp_check_module_loaded(fname_list):`
`100`	`101`	`"""`
`101`	`102`	`Check if this module is loaded`
`102`	`103`	`"""`
`103`		`-result= []`
`104`		`-forfnameinfname_list:`
`105`		`-iffnameinglobals():`
`106`		`-result.append(True)`
`107`		`-else:`
`108`		`-result.append(False)`
	`104`	`+result= [Trueiffnameinglobals()elseFalseforfnameinfname_list]`
	`105`	`+`
`109`	`106`	`returnresult`

`‎python/visualizationCommand.py‎`

Lines changed: 4 additions & 6 deletions

Original file line number	Diff line number	Diff line change
`@@ -7,12 +7,10 @@ def _vp_seaborn_show_values(axs, precision=1, space=0.01):`
`7`	`7`	`pstr='{:.'+str(precision)+'f}'`
`8`	`8`
`9`	`9`	`def_single(ax):`
`10`		`-# check orient`
	`10`	`+# check orient / if 0`
`11`	`11`	`orient='v'`
`12`		`-iflen(ax.patches)==1:`
`13`		`-# check if 0`
`14`		`-ifax.patches[0].get_x()==0:`
`15`		`-orient='h'`
	`12`	`+iflen(ax.patches)==1andax.patches[0].get_x()==0:`
	`13`	`+orient='h'`
`16`	`14`	`else:`
`17`	`15`	`# compare 0, 1 patches`
`18`	`16`	`p0=ax.patches[0]`
`@@ -36,7 +34,7 @@ def _single(ax):`
`36`	`34`	`ax.text(_x,_y,value,ha='left')`
`37`	`35`
`38`	`36`	`ifisinstance(axs,_vp_np.ndarray):`
`39`		`-foridx,axin_vp_np.ndenumerate(axs):`
	`37`	`+for_,axin_vp_np.ndenumerate(axs):`
`40`	`38`	`_single(ax)`
`41`	`39`	`else:`
`42`	`40`	`_single(axs)`

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Commitf126071

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4 files changed

4 files changed

`‎python/pandasCommand.py‎`

`‎python/userCommand.py‎`

`‎python/variableCommand.py‎`

`‎python/visualizationCommand.py‎`

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