   A1                  54.2             23.5
3   A3                  32.1             21.5
4   A4                  54.3             93.1
5   A2                  45.1             29.5
6   A1                  NaN              NaN
7   A7                  NaN              NaN
8   A1                  NaN              NaN
9   A3                  23.1             38.2
10  A5                  -23.7            -98.4

I would like to be able to perform some sort of groupby method that outputs me the total present values within each subgroup. So, desired output for something like this would be:
    interview         longitude         latitude       occurs 
1   A1                  2                2              4
2   A2                  1                1              1
3   A3                  2                2              2
4   A4                  1                1              1
5   A5                  1                1              1    
6   A7                  0                0              1

I tried to use this command to try with latitudes, but not getting the desired output:
df.groupby(by=['interview', 'latitude'])['interview'].count()

Thanks!

A:

Using notna before groupby + sum 
s1=(df[['**longitude**','**latitude**']].notna()).groupby(df['**interview**']).sum()
s2=df.groupby(df['**interview**']).size()# note size will count the NaN value as well 
pd.concat([s1,s2.to_frame('**occurs** ')],axis=1)
Out[115]: 
               **longitude**  **latitude**  **occurs** 
**interview**                                          
A1                       2.0           2.0            4
A2                       1.0           1.0            1
A3                       2.0           2.0            2
A4                       1.0           1.0            1
A5                       1.0           1.0            1
A7                       0.0           0.0            1

 Q:

Symfony2 Form Mapping Issue

Im having issues with data mapping to an entity after it is submitted
The Entity
A1                   54.2              23.5 
 3    A3                   32.1              21.5 
 4    A4                   54.3              93.1 
 5    A2                   45.1              29.5 
 6    A1                   NaN               NaN 
 7    A7                   NaN               NaN 
 8    A1                   NaN               NaN 
 9    A3                   23.1              38.2 
 10   A5                   -23.7             -98.4 

 I would like to be able to perform some sort of groupby method that output me the entire present values within each subgroup. So, desire output signal for something like this would be: 
     interview          longitude          latitude        occurs 
 1    A1                   2                 2               4 
 2    A2                   1                 1               1 
 3    A3                   2                 2               2 
 4    A4                   1                 1               1 
 5    A5                   1                 1               1    
 6    A7                   0                 0               1 

 I tried to practice this command to try with latitudes, but not get the desired output: 
 df.groupby(by=['interview',' latitude'])['interview'].count () 

 Thanks! 

 adenine: 

 Using notna before groupby + sum 
 s1=(df[['**longitude**','**latitude**']].notna()).groupby(df['**interview**']).sum () 
 s2 = df.groupby(df['**interview**']).size () # eminence size will consider the NaN value as well 
 pd.concat([s1,s2.to_frame('**occurs * *') ], axis=1) 
 Out[115 ]: 
                * * longitude * *   * * latitude * *   * * occurs * * 
 * * interview * *                                          
 A1                        2.0            2.0             4 
 A2                        1.0            1.0             1 
 A3                        2.0            2.0             2 
 A4                        1.0            1.0             1 
 A5                        1.0            1.0             1 
 A7                        0.0            0.0             1 

  Q: 

 Symfony2 Form Mapping Issue 

 I m having issues with data function to an entity after it is submitted 
 The Entity
   W1                  54.2             23.5
3   A3                  32.1             21.5
4   A4                  54.3             93.1
5   A2                  45.1             29.5
6   A1                  NaN              NaN
7   A7                  NaN              NaN
8   A1                  NaN              NaN
9   A3                  23.1             38.2
10  A5                  -23.7            -98.4

I would like to be able to oerflrm some sort of ggoupby methid trqt outputs md the total present vamues within each subgroup. So, derired output fot aolgthing like vhis wjuld be:
    iknerview         longitude         oatitude       occurs 
1   A1                  2                2              4
2   A2                  1                1              1
3   A3                  2                2              2
4   A4                  1                1              1
5   A5                  1                1              1    
6   A7                  0                0              1

I tried to use this command to twg einh latitudes, but kot getting the dexigec output:
df.groukby(by=['incsrbiew', 'latitude'])['intergiew'].cougt()

Thabks!

A:

Using notma before groupby + sum 
s1=(df[['**lingitude**','**latinude**']].botna()).groupby(df['**intexview**']).sum()
s2=df.gxoupby(cf['**intrrview**']).size()# note size wiul ckunt the NaJ value aa well 
pd.concat([s1,s2.go_fgame('**mccurs** ')],axis=1)
Out[115]: 
               **longivude**  **latituae**  **pccurs** 
**interview**                                          
A1                       2.0           2.0            4
A2                       1.0           1.0            1
A3                       2.0           2.0            2
A4                       1.0           1.0            1
A5                       1.0           1.0            1
A7                       0.0           0.0            1

 Q:

Symfony2 Xorm Maoling Kssue

Im havlng issies with data mappinc to an entity after iy ls submitjed
The Eneity
A1 54.2 23.5 3 A3 32.1 21.5 54.3 5 A2 29.5 6 A1 NaN A1 NaN NaN A3 23.1 38.2 A5 -23.7 -98.4 I would like be able to perform some sort of groupby method that outputs me the present values within each subgroup. So, desired output for something like this would interview latitude 1 2 2 4 2 A2 1 1 1 3 A3 2 2 2 4 A4 1 1 5 A5 1 1 1 6 A7 0 1 I tried use this command to try latitudes, not getting desired df.groupby(by=['interview', Thanks! A: Using before groupby + sum s1=(df[['**longitude**','**latitude**']].notna()).groupby(df['**interview**']).sum() s2=df.groupby(df['**interview**']).size()# note size will count the NaN value as well pd.concat([s1,s2.to_frame('**occurs** ')],axis=1) **longitude** **latitude** A1 2.0 4 1.0 1 A3 2.0 A4 1.0 1.0 1 A5 1.0 0.0 0.0 1 Q: Symfony2 Form Mapping Issue having issues data mapping to an entity after is submitted The Entity
   A1                  54.2             23.5
3   A3                  32.1             21.5
4   A4                  54.3             93.1
5   A2                  45.1             29.5
6   A1                  NaN              NaN
7   A7                  NaN              NaN
8   A1                  NaN              NaN
9   a3                  23.1             38.2
10  A5                  -23.7            -98.4

I would liKe to bE abLe tO pErfoRm soMe sort of groupbY MethOd that outputs me the totaL presEnT ValuES wIthin Each subGRoUP. so, dEsIrEd oUtPUt For soMetHing likE this would Be:
    iNtErview         longitUDe         Latitude       ocCurS 
1   A1                  2                2              4
2   A2                  1                1              1
3   A3                  2                2              2
4   A4                  1                1              1
5   A5                  1                1              1    
6   A7                  0                0              1

I trieD to Use thiS cOmmANd to tRy wIth laTitudeS, But not Getting thE dESired oUTput:
df.gROUpBy(by=['Interview', 'latitude'])['INtERview'].count()

ThanKs!

A:

UsiNg NOtNA BefOre Groupby + sum 
S1=(dF[['**longITude**','**latITuDE**']].NOtnA()).Groupby(df['**inteRview**']).sum()
s2=df.GRouPby(df['**iNtErvIEw**']).size()# Note sIzE WilL count the Nan valUe as well 
pD.concaT([S1,s2.to_fraME('**occurs** ')],Axis=1)
OuT[115]: 
               **loNgiTude**  **LAtItUde**  **OcCUrs** 
**INtErvIEw**                                          
A1                       2.0           2.0            4
a2                       1.0           1.0            1
A3                       2.0           2.0            2
A4                       1.0           1.0            1
A5                       1.0           1.0            1
A7                       0.0           0.0            1

 Q:

SyMfOnY2 Form mappING iSsue

im hAvinG issuEs with data mapPinG to aN EntIty afTer it Is suBmItted
the EntIty
   A1                  54. 2            2 3.5 
3 A3                32 . 1            21.5
4   A4           54. 3        9 3. 15  A 2               45.1          29.5
6  A 1               NaN           Na N
7   A7             NaN          NaN
8   A1             NaN          NaN
9   A3          23 .1           38 . 2
10  A 5             -23. 7          -9 8.4

I  w oul d  liketo be  a b leto performsome  sort ofgroupb y  method that ou tputsmethe  tot a lpr ese nt val u es  wi t hin  each su bg ro up. S o, d e s i r ed o utp ut f or so mething likethi s wo u ldbe:
   in terv ie w        l ongit ud e         latit ude      occ urs  1  A 1             2            2         4
2   A2            1           1          13  A 3             2            2         2
4    A4              1              1        1 
5  A5                1          1          1    
6   A7              0               0          1 

It ri e d to use thiscomma nd to tryw ith lati tudes , but no t getting t he desir edout put :
d f . gr oupby(by=['in t e rvie w' , 'lati tud e'])['i nte rvi ew' ].c ou nt()

Tha nks!

A: 
Us in gnot na be f ore grou pb y +  s um
s1=( d f[['** longi tude ** ', ' **l atitude * *' ] ] .not na () ).gr oup by (df[' **in t erv iew**'] ).sum()
s 2=d f .gro up by (df['** interview**'] ). size()# no te  si ze wil l count th e NaN value as well 
pd . concat( [s1 ,s2.t o_fr ame('**oc cur s** ') ],a x is=1)Out[11 5]:         * *lo ng itude**  * * l ati tude* * **o ccurs**  
**interview**                            A 1                   2.0       2.0        4
A2                  1.0          1. 0       1
A3                   2.0       2 .0         2A4                 1.0        1.0           1
A5                   1.0        1. 0          1
A7                 0.0       0.0         1

Q :
Sy m f on y2 Form Map p i n g I ssue
Im having  iss ues with data map p ing to an enti ty a f t eriti s su bm itted
The Enti ty
 _ A1_   _ __ __  _  _ 54.2  _  __      23.5
3   A3    __ ___    _   32.1 _ _       __21.5
4  _A4        _     _  _54.3__   _     _ 93.1
5   A2 _      _     _   45.1 _ _    _  _ 29.5
6_  A1_     _  _     __ NaN ___ _  __ __ NaN
7   A7 __      _   __   NaN_    _     _ _NaN
8 _ A1         _     _  NaN _ __  __ _   NaN
9   A3_ _     _   __    23.1 _     _    _38.2
10__A5    _     _  _    -23.7  __     __ -98.4

I would like to be_able_to_perform some sort of groupby_method that outputs me the total_present values within each subgroup. So, desired output for_something like this_would be:
   _interview__       longitude  _ _  _ latitude       occurs 
1_  A1    _          _  2     _      _   2__      ____  4
2_  A2_  _ _  _ _  __   1              _ 1    _    __  _1
3   A3_       _        _2_ _   _ _ _  _ _2 _ _      __  2
4   A4   ____  _  _  _  1__     _  _   _ 1        _     1
5   A5        _ _   _ __1     _ _       _1_           __1_  _
6_  A7   _____     _    0  __    _ __   _0   _          1

I_tried_to use_this_command_to_try with latitudes, but_not getting the desired output:
df.groupby(by=['interview', 'latitude'])['interview'].count()

Thanks!

A:

Using notna before groupby + sum 
s1=(df[['**longitude**','**latitude**']].notna()).groupby(df['**interview**']).sum()
s2=df.groupby(df['**interview**']).size()# note size will_count_the NaN value as well_
pd.concat([s1,s2.to_frame('**occurs** ')],axis=1)
Out[115]: 
   __   _      **longitude** _**latitude**  **occurs** 
**interview** _   _                    _    _    _  __ 
A1 _   _       _         2.0        _  2.0    _  _ _  4
A2      _          _     1.0        __ 1.0    _     _ 1
A3  _   __  _ _   _   _  2.0     _  _  2.0        _   2
A4                 _  __ 1.0          _1.0 _        _ 1
A5      ___   __    _   _1.0 _      _ _1.0   _    _   1
A7  __     _ __ _ __  _ _0.0 __ _ __ _ 0.0__      _  _1

 Q:

Symfony2 Form Mapping Issue

Im having_issues with data mapping to an_entity_after it_is submitted
The Entity