Question

如果满足特定条件，我需要用户确认离开页面。问题是位置更改不等待对话框让用户回答。

这是我的代码：

角度模块1：

...
function confirmLeavePage(e, newUrl) {
        if(form.cod.value) {
            customDialog.confirmDialog('Title','Leave?').then(
            function(){
                console.log('go to selected page');
            },function(){
                e.preventDefault();
            });
        }
    }

    $scope.$on("$locationChangeStart", confirmLeavePage);
...

角度模块2：

angular.module('dialog').service('customDialog', function($mdDialog, $q, $location) {

    this.confirmDialog = function(title, content){
        var deferred = $q.defer();
        $mdDialog.show($mdDialog.confirm({
            templateUrl:'confirmDialog.html',
            title : title,
            textContent : content,
            ok : 'Confirm',
            cancel: 'Cancel'
        })).then(function() {
            console.log('confirmed');
            deferred.resolve();
        }, function() {
           console.log('abort');
           deferred.reject();
        });
        return deferred.promise; 
    }


});

有什么想法吗？

Answer 1

试试这个

#reshape datetime columns to one, create datetimeindex
df1 = pd.melt(df.reset_index(), id_vars=['EMI', 'index'], value_name='date')
        .set_index('date')
#convert index to periodindex by month
df1.index = pd.to_datetime(df1.index, format='%d/%m/%y', errors='coerce')
              .to_period('M') 
#groupby by column index nad resample by month 
df1 = df1.groupby('index')
         .resample('M')
         .ffill()
         .drop(['variable', 'index'], axis=1)
         .reset_index()
#pivoting, fill NaN with 0, cast floats to int
df1 = df1.pivot(index='index', columns='date', values='EMI')
         .fillna(0)
         .astype(int)
#change format of columns
df1.columns = df1.columns.strftime('%m/%y')
#concat original dataframe
df = pd.concat([df,df1], axis=1)

print (df)
  Start Date  End Date   EMI  07/15  08/15  09/15  10/15  11/15  12/15  01/16  \
0   01/12/16  01/12/17  4800      0      0      0      0      0      0      0   
1   09/01/16  09/01/17  3000      0      0      0      0      0      0   3000   
2   01/07/15  01/05/16  2300   2300   2300   2300   2300   2300   2300   2300   

   03/17  04/17  05/17  06/17  07/17  08/17  09/17  10/17  11/17  12/17  
0  ...     4800   4800   4800   4800   4800   4800   4800   4800   4800   4800  
1  ...        0      0      0      0      0      0      0      0      0      0  
2  ...        0      0      0      0      0      0      0      0      0      0  

[3 rows x 33 columns]

事件不等待用户在对话框内回答

1 个答案: