hopefully you can help me.
I have created a dataframe with 25 columns, rows are empty so far.
column_name = df[0].values.tolist()[0:25]
column_name
['Time:',
'\tDC_Verbrauch:',
'\tDC_Verbrauch_Ueberlauf:',
'\tHVEM_IstLeistungNA:',
'\tHVLM_Restladezeit_HV_Bat_02:',
'\tHVLM_Bat_laden_aktiv:',
'\tHVLM_Ladeart:',
'\tHVLM_Stecker_Status:',
'\tKBI_angez_Geschw:',
'\tKBI_Inhalt_Tank:',
'\tKBI_Aussen_Temp_gef:',
'\tMO_KVS:',
'\tMO_KVS_Ueberlauf:',
'\tMO_Verbrauch_EM_Ges:',
...
Then deleted the \t and put these list of 25 values as column names of an empty dataframe.
Now I have a list that contains 16350 values.
Every 25th value should start a new row. Which means I will have later have 654 rows with 25 filled columns. So from list shape (16350,1) to a dataframe (654,25)
values
['1654786811.282628',
'786Unit_WattSecond',
'0',
'13700Unit_Watt',
'1370Unit_Minut',
'0',
'2',
'2',
...
'1810Unit_WattSecond',
'0',
'1654786811.381790',
'83Unit_WattSecond',
'1',
'4150Unit_Watt',
'415Unit_Minut',
'1',
'3',
'3',
'26.56Unit_KiloMeterPerHour',
The beginning of the first row is '1654786811.282628' - Beginning of the second: '1654786811.381790'
So I need a row-whise filling of a dataframe out of one list of values.
Best Regards thaclone
CodePudding user response:
you can use numpy.reshape to achieve that.
See on a simpler data of 3 columns:
data = [ "Tom", 32, 85, "Jerry", 35, 50, "Mickey", 40, 10, "Mouse", 20, 12 ]
pd.DataFrame(np.array(data).reshape(4,3), columns = ["name", "age", "height"])