How to convert Pandas object and not the entire dataframe to string?

Question

While reading the csv file, I am iterating over it using itertuples :

df = pd.read_csv("/home/aviral/dev/misc/EKYducHrK93oSKCt7nY0ZYne.csv", encoding='utf-8')
count = 0
for row in df.itertuples():
    print (row)
    if count == 0:
        sys.exit()
    count += 1

The value of row is:

Pandas(Index=0, _1='07755aa8-3a15-42ca-8757-58da8a9a298f', _2=nan,
_3='07755aa8-3a15-42ca-8757-58da8a9a298f', _4='2018-03-14T04:43:21.309Z', _5='2018-03-14T04:43:30.679Z', _6='2018-03-14T04:43:30.679Z', User='Vaibhav Inzalkar', Username=919766148649, _9=24, _10=24, _11='Android',
_12='6E6498d700e51ebf', _13='2.3.0', _14='2.3.0', _15=nan, Tags=nan, vill_name='911B675b-B422-41E9-A2ae-6Ccb1e9de2e4', vill_name_parent_response_id='02d93f9d-80df-4e12-8c6b-4c7859a50862', vill_name_taluka_code=4082, census_district_2011='Yavatmal', vill_name_gp_code=194782, vill_name_village_code=542432.0, subdistrict_code=4082, vill_name_anganwadi_code=27510160609.0, census_village_sd_2011='Dhamani', district_code=510, vill_name_taluka_name='Yavatmal', vill_name_gp_name='Dhamni', vill_name_staffname='Anjali Rajendra Pachkawade', vill_name_gram_panchayat_survey_phase='Phase_3', census_subdistrict_2011='Yavatmal', vill_name_auditor_mobile_number=919766148649, vill_name_auditor_name='Vaibhav Inzalkar', vill_name_dist_sd_vill_comb_code=5104082194782542848, vill_name_anganwadi_worker_mobile_number=9404825268.0, _36=nan, buildtype='Pucca House', buildown='Temporary Arrangement', _39=1,
_40=1, staffname='Anjali Rajendra Pachakawde', anganwadi_sevika_own_mobile_yn=nan, anganwadi_worker_mobile_number=nan, wrkrvillyn='Yes', sahayakname='Pandharnishe Madam', helpervillyn='Yes', pregno=6, mothlactano=6, _49=1, imr_child_birth=3, imr_child_deaths=1, child0to6no=43, _53=1.0, angawadi_children_not_suffering_from_sam_age_zero_six=42.0, _55=0.0, adolegirlno=0, _57=nan, _58=1, _59=1, _60=1, _61=0, _62=1, _63=0,
_64=1, _65=1, _66=0, _67=0, _68=0, _69=0, _70=0, _71=0, _72=0, _73=0, _74=0, _75=0, _76=1, _77=0, _78=0, drugs_nothing=0, drugs_nothing_646PdPW9FewY3edC2LeG=0, _81=0, _82=0, _83=0, _84=0,
_85=0, _86=1, _87=1, _88=0, _89=0, _90=0, _91=0, _92=0, _93=0, _94=0, _95=0, _96=0, infraphy_nota=0, basic_util_awc_Register=0, _99=1, _100=1, _101=0, _102=0, _103=0, basic_util_awc_Ventilation=0, _105=0, _106=1, _107=1, _108=1, _109=1, basic_util_awc_Phenyl=1, basic_util_awc_Register_2DN84oFiz565JzqFegx7=0, _112=0, _113=0,
_114=0, _115=0, _116=0, basic_util_awc_Ventilation_2DN84oFiz565JzqFegx7=0, _118=0, _119=0,
_120=0, _121=0, _122=0, basic_util_awc_Phenyl_2DN84oFiz565JzqFegx7=0, basic_util_awc_nota=0, solar_unit=nan, elec_bill_paid=nan, _127=nan,
_128=nan, _129=nan, _130=nan, _131=nan, _132=nan, _133=nan, _134=nan, _135=nan, _136=nan, other=nan, _138=1, _139=1, _140=1, _141=1, _142=1, _143=1, _144=1, _145=0, _146=0, _147=0, _148=0, _149=0, _150=0, _151=0, servpregbaby03_nota=0, anganwadi_children_vaccination_BCG=1.0, anganwadi_children_vaccination_DPT=1.0, anganwadi_children_vaccination_OPV=1.0, _156=0.0, anganwadi_children_vaccination_Measles=1.0, _158=1.0, _159=1.0,
_160=0.0, _161=0.0, _162=0.0, anganwadi_children_vaccination_nota=0.0, _164=1, _165=1, _166=1, _167=1, _168=0, _169=0, _170=0, _171=0, servchild3to6_nota=0, servadolgirl_registration=0, _174=0, _175=0,
_176=0, _177=0, servadolgirl_registration_KoXmKreRO4DAxGuLelRP=0, _179=0, _180=0, _181=0, _182=0, servadolgirl_nothing=0, servadolgirl_nothing_KoXmKreRO4DAxGuLelRP=1, anganwadi_photo='Https://Collect-V2-Production.s3.Ap-South-1.Amazonaws.com/Omurh3lmkcmftts4muxn%2Fwmse68bvz5zwmzcfj9tx%2Fcpo0bvh0kuday74e9cqw%2F94c13850-6008-4087-B742-7B31ad2e4d02.Jpeg', anganwadi_map_latitude=20.338352399999998, anganwadi_map_longitude=78.1930695, anganwadi_map_accuracy=10.0,
_189=nan, problem_1='1)Pakki Building', problem_2='1) Toilet', problem_3='Kichan', problem_4='Elictric Line', problem_5='Water Connection', popserv=55, census_country='India', state_name='Maharashtra', state_code=27, sc_ang_id=1, village_code_census2011_raw=542432.0, phase='Phase 3')

How can I get just the columns and the values? Something just like this:

_1='07755aa8-3a15-42ca-8757-58da8a9a298f', _2=nan, _3='07755aa8-3a15-42ca-8757-58da8a9a298f', _4='2018-03-14T04:43:21.309Z', _5='2018-03-14T04:43:30.679Z', _6='2018-03-14T04:43:30.679Z', User='Vaibhav Inzalkar', Username=919766148649, _9=24, _10=24, _11='Android',
_12='6E6498d700e51ebf', _13='2.3.0', _14='2.3.0'

Answer 1

Something like this?

Sample dataframe

  name city  cell
0    A    X   124
1  ABC    Y   345
2  BAD    Z    76

Code:

for i in df.itertuples():
    # Python 3.6
    print(','.join(f' {j}="{getattr(i,j)}"' for j in df.columns))
    # Python 3.5
    print(','.join(' {0}="{1}"'.format(j, getattr(i,j)) for j in df.columns))

Output:

name="A", city="X", cell="124"
name="ABC", city="Y", cell="345"
name="BAD", city="Z", cell="76"

Writing to file:

with open("dummy.json", "a+") as f:
    for i in df.itertuples():
        x = dict(i._asdict())
        json.dump(x, f)
        f.write("\n")