Upload 4 files
Browse files- SampleSubmission.csv +5178 -0
- Test.csv +0 -0
- Train.csv +0 -0
- covid_tweets.py +86 -0
SampleSubmission.csv
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|
3680 |
+
PBMB074V,0
|
3681 |
+
PC0IRBWY,0
|
3682 |
+
PC4PS2ZF,0
|
3683 |
+
PCBZXQQQ,0
|
3684 |
+
PCKSLBYT,0
|
3685 |
+
PCM627DD,0
|
3686 |
+
PCQJFCP3,0
|
3687 |
+
PD02IQLO,0
|
3688 |
+
PD3O5GNH,0
|
3689 |
+
PE7NDCPY,0
|
3690 |
+
PEY3QAID,0
|
3691 |
+
PFOMH8PN,0
|
3692 |
+
PFTTACWE,0
|
3693 |
+
PG00UBZ4,0
|
3694 |
+
PG676RR1,0
|
3695 |
+
PGRQTX07,0
|
3696 |
+
PHEDMQYS,0
|
3697 |
+
PHJCVC71,0
|
3698 |
+
PHTGRB0L,0
|
3699 |
+
PHZV1HBZ,0
|
3700 |
+
PI0TIK1D,0
|
3701 |
+
PIFJZC9Z,0
|
3702 |
+
PIR3V9QJ,0
|
3703 |
+
PJHH73T1,0
|
3704 |
+
PJL47PXC,0
|
3705 |
+
PJNIJ6AT,0
|
3706 |
+
PJNVJ223,0
|
3707 |
+
PJSISN1Q,0
|
3708 |
+
PJVTNMD0,0
|
3709 |
+
PKK73W2K,0
|
3710 |
+
PL0RHMZW,0
|
3711 |
+
PL5UIEY6,0
|
3712 |
+
PLFA5S28,0
|
3713 |
+
PLJHSCFU,0
|
3714 |
+
PLJN1GMB,0
|
3715 |
+
PM3CKM16,0
|
3716 |
+
PM514NOL,0
|
3717 |
+
PM7IBUCZ,0
|
3718 |
+
PMUOB5IK,0
|
3719 |
+
PMY3J6Y9,0
|
3720 |
+
PN1TZB52,0
|
3721 |
+
PN8X0WC4,0
|
3722 |
+
PNBNWX54,0
|
3723 |
+
PNRB1OOR,0
|
3724 |
+
PNRX2FHW,0
|
3725 |
+
PO2KNCX8,0
|
3726 |
+
PO7PXS51,0
|
3727 |
+
POP6BRIT,0
|
3728 |
+
PP65E7X4,0
|
3729 |
+
PPAEXKBV,0
|
3730 |
+
PPDN4KZB,0
|
3731 |
+
PPFJ9TVN,0
|
3732 |
+
PPIFNGEO,0
|
3733 |
+
PPR9U53D,0
|
3734 |
+
PPTUII1P,0
|
3735 |
+
PQ4OJPZQ,0
|
3736 |
+
PR8PS44D,0
|
3737 |
+
PRWKVP4H,0
|
3738 |
+
PS2P5MWA,0
|
3739 |
+
PSEJ49ZR,0
|
3740 |
+
PSJJO5DP,0
|
3741 |
+
PT2USMYE,0
|
3742 |
+
PT346YTU,0
|
3743 |
+
PT81EM0M,0
|
3744 |
+
PTAMZ7JY,0
|
3745 |
+
PTCQF6MM,0
|
3746 |
+
PTOGAA86,0
|
3747 |
+
PTTE0YC7,0
|
3748 |
+
PTXQYSOD,0
|
3749 |
+
PU113FKQ,0
|
3750 |
+
PU5Z3LV4,0
|
3751 |
+
PUA79MJL,0
|
3752 |
+
PUDS72Q5,0
|
3753 |
+
PUHDELMO,0
|
3754 |
+
PUI0S3HK,0
|
3755 |
+
PVIDP7QI,0
|
3756 |
+
PVR614Z3,0
|
3757 |
+
PVSFEXGY,0
|
3758 |
+
PVZPB0SR,0
|
3759 |
+
PWG2AW28,0
|
3760 |
+
PWK06ETM,0
|
3761 |
+
PWZ6YEHA,0
|
3762 |
+
PX4OS8CS,0
|
3763 |
+
PX7ARVY4,0
|
3764 |
+
PXCO8JHZ,0
|
3765 |
+
PXSFDNUT,0
|
3766 |
+
PY1WKNE7,0
|
3767 |
+
PY83QTDA,0
|
3768 |
+
PYQG73LI,0
|
3769 |
+
PYYRYLFP,0
|
3770 |
+
PZ24GRHK,0
|
3771 |
+
PZ55C90G,0
|
3772 |
+
PZ9K7ILW,0
|
3773 |
+
PZB3RXAF,0
|
3774 |
+
PZDGDBHS,0
|
3775 |
+
PZF2ROO4,0
|
3776 |
+
PZV8Z555,0
|
3777 |
+
Q01H8CZ8,0
|
3778 |
+
Q0B0HJQH,0
|
3779 |
+
Q0H402GU,0
|
3780 |
+
Q0IYG36R,0
|
3781 |
+
Q145WNWG,0
|
3782 |
+
Q15HRERT,0
|
3783 |
+
Q244Y3L8,0
|
3784 |
+
Q2IVHW5C,0
|
3785 |
+
Q2Y3D95L,0
|
3786 |
+
Q2Y79W51,0
|
3787 |
+
Q322GUTO,0
|
3788 |
+
Q33NDAER,0
|
3789 |
+
Q3R3GIR5,0
|
3790 |
+
Q3XB0G26,0
|
3791 |
+
Q3YSAL67,0
|
3792 |
+
Q4EOJIPT,0
|
3793 |
+
Q4FJQB5P,0
|
3794 |
+
Q58YA0C0,0
|
3795 |
+
Q5MD9OB7,0
|
3796 |
+
Q5NGAOYX,0
|
3797 |
+
Q5NUC5GG,0
|
3798 |
+
Q5X5MIKT,0
|
3799 |
+
Q652SSYD,0
|
3800 |
+
Q67EGSE1,0
|
3801 |
+
Q6C88X2A,0
|
3802 |
+
Q6GH7DYD,0
|
3803 |
+
Q6LSNHUU,0
|
3804 |
+
Q6PLNXT6,0
|
3805 |
+
Q6QV7L2Q,0
|
3806 |
+
Q7C1ZXKF,0
|
3807 |
+
Q7GBSJUW,0
|
3808 |
+
Q7UAFFU0,0
|
3809 |
+
Q84ZK7GP,0
|
3810 |
+
Q89A3JPX,0
|
3811 |
+
Q8OS73SU,0
|
3812 |
+
Q8Q8ZQ9J,0
|
3813 |
+
Q94YDAVA,0
|
3814 |
+
QA67DITE,0
|
3815 |
+
QBF48OCA,0
|
3816 |
+
QBLQWPL4,0
|
3817 |
+
QCD7D8G7,0
|
3818 |
+
QCH557SR,0
|
3819 |
+
QCKLSCS5,0
|
3820 |
+
QCLH7O2K,0
|
3821 |
+
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|
3822 |
+
QD1KL9OI,0
|
3823 |
+
QDNLHX4P,0
|
3824 |
+
QDWR725O,0
|
3825 |
+
QE0OSVN7,0
|
3826 |
+
QECQYUKM,0
|
3827 |
+
QEIBNTB8,0
|
3828 |
+
QEIF17D8,0
|
3829 |
+
QF15YIVT,0
|
3830 |
+
QFDJUVQ0,0
|
3831 |
+
QFJ0K3BR,0
|
3832 |
+
QFT64MP2,0
|
3833 |
+
QG5NQ6LA,0
|
3834 |
+
QGA9VBG7,0
|
3835 |
+
QGCS1ILL,0
|
3836 |
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QGMI7D6Q,0
|
3837 |
+
QGY367GF,0
|
3838 |
+
QH5P373L,0
|
3839 |
+
QH7CW468,0
|
3840 |
+
QHCFPUPX,0
|
3841 |
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QHIUXK7Q,0
|
3842 |
+
QHIX3PD5,0
|
3843 |
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QHXIPK2Y,0
|
3844 |
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QI749J8L,0
|
3845 |
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QI7IQ1XM,0
|
3846 |
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QIOUP883,0
|
3847 |
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QIPBE8PQ,0
|
3848 |
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QIYUZ597,0
|
3849 |
+
QJJ72WWX,0
|
3850 |
+
QJKBGEXM,0
|
3851 |
+
QJS0IK3S,0
|
3852 |
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QJVI52X0,0
|
3853 |
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QK2JP27M,0
|
3854 |
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QK6AB8I2,0
|
3855 |
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QKGFQCG8,0
|
3856 |
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QKN1C6GN,0
|
3857 |
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QKR3PGCD,0
|
3858 |
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QKUEWN76,0
|
3859 |
+
QKZNVFXS,0
|
3860 |
+
QLEXLO2Q,0
|
3861 |
+
QLL3TNGU,0
|
3862 |
+
QN5R9FC7,0
|
3863 |
+
QNA7ESY7,0
|
3864 |
+
QNHZM9OF,0
|
3865 |
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QNL0EAJ7,0
|
3866 |
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|
3867 |
+
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|
3868 |
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|
3869 |
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|
3870 |
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|
3871 |
+
QP5HG17I,0
|
3872 |
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|
3873 |
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QQDUIX1A,0
|
3874 |
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QQJD23FC,0
|
3875 |
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|
3876 |
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|
3877 |
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QRC07SXQ,0
|
3878 |
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QRPX9ZJM,0
|
3879 |
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|
3880 |
+
QS1ZSCKL,0
|
3881 |
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QSFLHGWN,0
|
3882 |
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QSQ669CA,0
|
3883 |
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|
3884 |
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QSZR48HM,0
|
3885 |
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QTGOZ0GS,0
|
3886 |
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|
3887 |
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|
3888 |
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QU7N5QBI,0
|
3889 |
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QUBG4LVH,0
|
3890 |
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QUETPBLE,0
|
3891 |
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|
3892 |
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QUQ408T7,0
|
3893 |
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|
3894 |
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|
3895 |
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|
3896 |
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|
3897 |
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|
3898 |
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|
3899 |
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|
3900 |
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|
3901 |
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QW7YMP7L,0
|
3902 |
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|
3903 |
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|
3904 |
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|
3905 |
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|
3906 |
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|
3907 |
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|
3908 |
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|
3909 |
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|
3910 |
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|
3911 |
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|
3912 |
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|
3913 |
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|
3914 |
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|
3915 |
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|
3916 |
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|
3917 |
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|
3918 |
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|
3919 |
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|
3920 |
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|
3921 |
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|
3922 |
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|
3923 |
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|
3924 |
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R34ZZQBO,0
|
3925 |
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|
3926 |
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|
3927 |
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|
3928 |
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|
3929 |
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R53IH7MA,0
|
3930 |
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R5EOU79T,0
|
3931 |
+
R5V0I4RI,0
|
3932 |
+
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|
3933 |
+
R6212VHR,0
|
3934 |
+
R680OSOV,0
|
3935 |
+
R6A5F893,0
|
3936 |
+
R6K028OK,0
|
3937 |
+
R6TEF1LL,0
|
3938 |
+
R72EBRQ8,0
|
3939 |
+
R7I9ARP6,0
|
3940 |
+
R7ILRP0E,0
|
3941 |
+
R7MXCZBD,0
|
3942 |
+
R7PQ27AC,0
|
3943 |
+
R7S34UX0,0
|
3944 |
+
R8BL25FT,0
|
3945 |
+
R8EH2T3H,0
|
3946 |
+
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|
3947 |
+
R8HGBUWB,0
|
3948 |
+
R8JB36V0,0
|
3949 |
+
R8JNZBNQ,0
|
3950 |
+
R8MSXMQ7,0
|
3951 |
+
R8VXHOAR,0
|
3952 |
+
R93NQV4V,0
|
3953 |
+
R9582DQM,0
|
3954 |
+
R991BVTR,0
|
3955 |
+
R9JJ8C5S,0
|
3956 |
+
RAKVFW8N,0
|
3957 |
+
RALA74GF,0
|
3958 |
+
RALE3UP3,0
|
3959 |
+
RAXP7EX9,0
|
3960 |
+
RB15QNY9,0
|
3961 |
+
RBBCO9CX,0
|
3962 |
+
RBGWT5FF,0
|
3963 |
+
RBNEI31E,0
|
3964 |
+
RBYPAF4K,0
|
3965 |
+
RC3TQ4VK,0
|
3966 |
+
RCBVX7CF,0
|
3967 |
+
RCK6BROS,0
|
3968 |
+
RCNOBF77,0
|
3969 |
+
RCQHZ993,0
|
3970 |
+
RCWTFGLU,0
|
3971 |
+
RCXXPDGM,0
|
3972 |
+
RCY3SLNE,0
|
3973 |
+
RCYIYPUF,0
|
3974 |
+
RCZN8QIT,0
|
3975 |
+
RDE95A6O,0
|
3976 |
+
RDVGA6YG,0
|
3977 |
+
REKZMO5C,0
|
3978 |
+
REO86Z48,0
|
3979 |
+
REY4W2DE,0
|
3980 |
+
RFAHGRYN,0
|
3981 |
+
RFHCT4CJ,0
|
3982 |
+
RG7IAP3R,0
|
3983 |
+
RG8PN7KY,0
|
3984 |
+
RGGV465A,0
|
3985 |
+
RGJTM4HJ,0
|
3986 |
+
RHAH6XXJ,0
|
3987 |
+
RHFQ3D7M,0
|
3988 |
+
RHHIVWQ1,0
|
3989 |
+
RHILAHIQ,0
|
3990 |
+
RHSKIOGR,0
|
3991 |
+
RHW7C3YG,0
|
3992 |
+
RI7MVT1U,0
|
3993 |
+
RI8OTYVG,0
|
3994 |
+
RIJ81BJN,0
|
3995 |
+
RIX18QF8,0
|
3996 |
+
RJ7EN7BN,0
|
3997 |
+
RJJQJZVC,0
|
3998 |
+
RK6WYK1R,0
|
3999 |
+
RKB073JE,0
|
4000 |
+
RKDSR06Z,0
|
4001 |
+
RKVIF36D,0
|
4002 |
+
RL6TJFU9,0
|
4003 |
+
RLRJLX2M,0
|
4004 |
+
RLSMG4EO,0
|
4005 |
+
RLYV3VRX,0
|
4006 |
+
RM0NQ73C,0
|
4007 |
+
RM4I4OKM,0
|
4008 |
+
RMFV40UE,0
|
4009 |
+
RN8EAI10,0
|
4010 |
+
RNRL05BQ,0
|
4011 |
+
RO4FYH01,0
|
4012 |
+
ROUTG5J2,0
|
4013 |
+
ROW958C5,0
|
4014 |
+
ROXQCBQC,0
|
4015 |
+
RP5NPUDM,0
|
4016 |
+
RQIXRVP4,0
|
4017 |
+
RQNVWZ12,0
|
4018 |
+
RR10902P,0
|
4019 |
+
RR2SBI7T,0
|
4020 |
+
RR4EM203,0
|
4021 |
+
RRU9GSR1,0
|
4022 |
+
RRZS9UDP,0
|
4023 |
+
RSDUKRJ6,0
|
4024 |
+
RSF2S9D4,0
|
4025 |
+
RTFYHF74,0
|
4026 |
+
RTG0DINW,0
|
4027 |
+
RTJHYTH7,0
|
4028 |
+
RTP7PID5,0
|
4029 |
+
RTRNUTHG,0
|
4030 |
+
RU1QHDNE,0
|
4031 |
+
RUJ5VXPF,0
|
4032 |
+
RUQC5PG0,0
|
4033 |
+
RUTCB0BF,0
|
4034 |
+
RUW0P5VN,0
|
4035 |
+
RV4516F7,0
|
4036 |
+
RV6X3QQ2,0
|
4037 |
+
RVHKP9CC,0
|
4038 |
+
RVTNA5B4,0
|
4039 |
+
RW2N3W74,0
|
4040 |
+
RWJHBLAP,0
|
4041 |
+
RWN11TQI,0
|
4042 |
+
RWTH74AN,0
|
4043 |
+
RYDCI29D,0
|
4044 |
+
RYI7ZQ9P,0
|
4045 |
+
RYLOMATL,0
|
4046 |
+
RZ2U6E6N,0
|
4047 |
+
RZ4RJES9,0
|
4048 |
+
RZDFOPZ7,0
|
4049 |
+
RZFV939G,0
|
4050 |
+
RZHO1PMF,0
|
4051 |
+
RZQ9XCEI,0
|
4052 |
+
RZQCJRMR,0
|
4053 |
+
RZWP38OR,0
|
4054 |
+
S07UUUKM,0
|
4055 |
+
S09F20XP,0
|
4056 |
+
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|
4057 |
+
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|
4058 |
+
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|
4059 |
+
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|
4060 |
+
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|
4061 |
+
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|
4062 |
+
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|
4063 |
+
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|
4064 |
+
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|
4065 |
+
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|
4066 |
+
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|
4067 |
+
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|
4068 |
+
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|
4069 |
+
S3UOJ6TB,0
|
4070 |
+
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|
4071 |
+
S54GTUFL,0
|
4072 |
+
S55G0YMK,0
|
4073 |
+
S5705NGW,0
|
4074 |
+
S5B77Y2C,0
|
4075 |
+
S68XBO6C,0
|
4076 |
+
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4077 |
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4079 |
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4080 |
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4081 |
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4082 |
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4084 |
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4085 |
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4086 |
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4087 |
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4088 |
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4089 |
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4090 |
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4092 |
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4094 |
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4097 |
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4101 |
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4110 |
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4112 |
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4119 |
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4144 |
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4145 |
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4210 |
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4211 |
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4212 |
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4213 |
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4214 |
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4215 |
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4216 |
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4217 |
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4218 |
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4219 |
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4220 |
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4224 |
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4225 |
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4230 |
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4232 |
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4260 |
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4261 |
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4264 |
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4265 |
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4266 |
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4270 |
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4275 |
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4280 |
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4299 |
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4300 |
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4309 |
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4310 |
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4311 |
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4313 |
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4314 |
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4315 |
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4317 |
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4320 |
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4325 |
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4330 |
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4332 |
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4340 |
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4410 |
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4423 |
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4426 |
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4427 |
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4428 |
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4429 |
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4430 |
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4431 |
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4432 |
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4433 |
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4434 |
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4435 |
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4436 |
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4438 |
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4441 |
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4444 |
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4460 |
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4472 |
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|
4474 |
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Test.csv
ADDED
The diff for this file is too large to render.
See raw diff
|
|
Train.csv
ADDED
The diff for this file is too large to render.
See raw diff
|
|
covid_tweets.py
ADDED
@@ -0,0 +1,86 @@
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|
1 |
+
import pandas as pd
|
2 |
+
import numpy as np
|
3 |
+
import streamlit as st
|
4 |
+
import altair as alt
|
5 |
+
|
6 |
+
from textblob import TextBlob
|
7 |
+
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
|
8 |
+
|
9 |
+
# Functions
|
10 |
+
def convert_to_df(sentiment):
|
11 |
+
sentiment_dict = {"polarity":sentiment.polarity,"subjectivity":sentiment.subjectivity}
|
12 |
+
sentiment_df = pd.DataFrame(sentiment_dict.items(),columns=["metric","value"])
|
13 |
+
return sentiment_df
|
14 |
+
|
15 |
+
def analyze_token_sentiment(docx):
|
16 |
+
analyzer = SentimentIntensityAnalyzer()
|
17 |
+
pos_list = []
|
18 |
+
neg_list = []
|
19 |
+
neu_list = []
|
20 |
+
for i in docx.split():
|
21 |
+
res = analyzer.polarity_scores(i)["compound"]
|
22 |
+
if res >= 0.1:
|
23 |
+
pos_list.append(i)
|
24 |
+
pos_list.append(res)
|
25 |
+
|
26 |
+
elif res <= -0.1:
|
27 |
+
neg_list.append(i)
|
28 |
+
neg_list.append(res)
|
29 |
+
else:
|
30 |
+
neu_list.append(i)
|
31 |
+
|
32 |
+
result = {"positives":pos_list, "negatives":neg_list, "neutral":neu_list}
|
33 |
+
return result
|
34 |
+
|
35 |
+
def main():
|
36 |
+
st.title("Sentiment Analysis NLP App using Streamlit")
|
37 |
+
st.subheader("Reformation Team Project")
|
38 |
+
|
39 |
+
menu = ["Home","About"]
|
40 |
+
choice = st.sidebar.selectbox("Menu",menu)
|
41 |
+
|
42 |
+
if choice == "Home":
|
43 |
+
st.subheader("Home")
|
44 |
+
with st.form(key="nlpForm"):
|
45 |
+
raw_text = st.text_area("Enter Text Here")
|
46 |
+
submit_button = st.form_submit_button(label="Analyze")
|
47 |
+
|
48 |
+
#layout
|
49 |
+
col1, col2 = st.columns(2)
|
50 |
+
if submit_button:
|
51 |
+
|
52 |
+
with col1:
|
53 |
+
st.info("Results")
|
54 |
+
sentiment = TextBlob(raw_text).sentiment
|
55 |
+
st.write(sentiment)
|
56 |
+
|
57 |
+
#Emoji
|
58 |
+
if sentiment.polarity > 0:
|
59 |
+
st.markdown("Sentiment:: Positive :smiley: ")
|
60 |
+
elif sentiment.polarity <0:
|
61 |
+
st.markdown("Sentiment:: Negative :angry: ")
|
62 |
+
else:
|
63 |
+
st.markdown("Sentiment:: Neutral :😐: ")
|
64 |
+
|
65 |
+
# Dataframe
|
66 |
+
result_df = convert_to_df(sentiment)
|
67 |
+
st.dataframe(result_df)
|
68 |
+
|
69 |
+
# Visualization
|
70 |
+
c = alt.Chart(result_df).mark_bar().encode(
|
71 |
+
x="metric",
|
72 |
+
y="value",
|
73 |
+
colour="metric")
|
74 |
+
st.altair_chart(c,use_container_width=True)
|
75 |
+
|
76 |
+
with col2:
|
77 |
+
st.info("Token Sentiment")
|
78 |
+
|
79 |
+
token_sentiments = analyze_token_sentiment(raw_text)
|
80 |
+
st.write(token_sentiments)
|
81 |
+
|
82 |
+
else:
|
83 |
+
st.subheader("About")
|
84 |
+
|
85 |
+
if __name__ == "__main__":
|
86 |
+
main()
|