read_csv parse mixed float and int column #1705
Description
Modin version: 0.7.4
pandas version compared to: 1.0.3
When reading csv with columns which are both ints and floats, I get a doubling of headers:
minimal.csv (from https://github.com/aalto-trafficsense/public-transport-dataset/blob/master/csv/device_data.csv)
"time","device_id","lat","lng","accuracy","activity_1","activity_1_conf","activity_2","activity_2_conf","activity_3","activity_3_conf"
"2016-08-26 09:00:00.206",2,60.186805,24.821049,33.6080017089844,"STILL",75,"IN_VEHICLE",5,"ON_BICYCLE",5
"2016-08-26 09:00:05.428",5,60.192928,24.767222,5,"WALKING",62,"ON_BICYCLE",29,"RUNNING",6
"2016-08-26 09:00:05.818",1,60.166382,24.700443,3,"WALKING",75,"IN_VEHICLE",5,"ON_BICYCLE",5
"2016-08-26 09:00:15.816",1,60.166254,24.700671,3,"WALKING",75,"IN_VEHICLE",5,"ON_BICYCLE",5
"2016-08-26 09:00:16.413",5,60.193055,24.767427,5,"WALKING",85,"ON_BICYCLE",15,"UNKNOWN",0
"2016-08-26 09:00:20.578",3,60.152996,24.745216,3.90000009536743,"STILL",69,"IN_VEHICLE",31,"UNKNOWN",0
Code to reproduce issue:
import pandas
import modin.pandas
df_modin = modin.pandas.read_csv('minimal.csv')
print(df_modin.head()) # 5 rows 22 columns
df_pandas = pandas.read_csv('minimal.csv')
print(df_modin.head()) # 5 rows 11 columns