Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf in 'y', tried every possible way

Here my dataset is pd and i have split it into training and testing data as pd_train1 and pd_train2

    sku national_inv lead_time in_transit_qty forecast_3_month forecast_6_month1 3921548            8        12              0                0                02 3191009           83         2             33              157              3773 2935810            8         4              0                0                04 2205847           31         4             63               70              1605 4953497            3        12              0                0                06 2286884            0         8              0                0                0  forecast_9_month sales_1_month sales_3_month sales_6_month sales_9_month min_bank1                0             1             1             2             5        22              603            44            98           148           156       533                0             0             0             1             1        04              223            27            90           164           219        05                0             0             0             0             0        06                0             0             0             0             0        0  potential_issue pieces_past_due perf_6_month_avg perf_12_month_avg local_bo_qty1               0               0             0.63              0.75            02               0               0             0.68              0.66            03               0               0             0.73              0.78            04               0               0             0.73              0.78            05               0               0             0.81              0.74            06               0               0             0.91              0.96            0  deck_risk oe_constraint ppap_risk stop_auto_buy rev_stop went_on_backorder  data1         0             0         0             1        0                No train2         0             0         0             1        0                No train3         0             0         0             1        0                No train4         0             0         1             1        0                No train5         0             0         0             1        0                No train6         0             0         0             1        0                No train

I wanted to create a lm model for my training data pd_train1But i am getting this error as below:

> fit=lm(went_on_backorder~.,data=pd_train1)Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :   NA/NaN/Inf in 'y'In addition: Warning message:In storage.mode(v) <- "double" : NAs introduced by coercion

I tried searching for infinite values:

sapply(pd_train1, function(x) sum(is.infinite(x)))             sku      national_inv         lead_time    in_transit_qty  forecast_3_month                 0                 0                 0                 0                 0  forecast_6_month  forecast_9_month     sales_1_month     sales_3_month     sales_6_month                 0                 0                 0                 0                 0     sales_9_month          min_bank   potential_issue   pieces_past_due  perf_6_month_avg                 0                 0                 0                 0                 0 perf_12_month_avg      local_bo_qty         deck_risk     oe_constraint         ppap_risk                 0                 0                 0                 0                 0     stop_auto_buy          rev_stop went_on_backorder              data                 0                 0                 0                 0 

And also for NA/NaN values in my training data on which i want to make linear model

     sku      national_inv         lead_time    in_transit_qty  forecast_3_month                 0                 0                 0                 0                 0  forecast_6_month  forecast_9_month     sales_1_month     sales_3_month     sales_6_month                 0                 0                 0                 0                 0     sales_9_month          min_bank   potential_issue   pieces_past_due  perf_6_month_avg                 0                 0                 0                 0                 0 perf_12_month_avg      local_bo_qty         deck_risk     oe_constraint         ppap_risk                 0                 0                 0                 0                 0     stop_auto_buy          rev_stop went_on_backorder                 0                 0                 0 Inf %in% pd_train1$went_on_backorder1] FALSENaN %in% pd_test$went_on_backorder1] FALSE

Henceforth I am not able to get the NA/NaN/Inf values in my datasetCan someone help me understand why is this throwing an error, please?Here went_on_backorder is my target variable.