Question

Python with Pandas dataframe

I have a csv file that contains a large number of columns and rows. I need to write a script that concatenates some elements of the first row with some elements of the 2 row. Something like # if data[1][0] starts with ch then concatenate the element right below it. I have attached a picture of just a sample of my data. The booleans have to stay on there as is. But I must drop the empty columns. I'm just having difficulty doing this through using pandas dataframe. In order for me to run the debugger on my script I must run a main.py that is under my tools folder. Any help would be appreciated.

chla chla chla chla chla chla chla chla chla chla chla chla isma::cas_ism _cmd_mode_cmd_mode_cmd_modefcp::afcs_fafcp::pfcs_facp::pfcs_dgosma::rti_ica::sys_time_a::cas_fail_a::att_fail_ipfcp::direct_mode single boolean boolean boolean boolean boolean boolean uint32 uint32 boolean boolean boolean 11.42644024 0 0 0 0 0 13 6.22E+08 0 0 0 11.42591953 0 0 1 0 0 0 14 6.22E+08 0 0 11.4253931 0 0 1 0 0 0 15 6.22E+08 0 0 ch1b ch1b ch1b isma::cas_isrcmd_mode.cmd_mode.. single boolean boolean 11.42644 0 11.42592 0 11.42539 0 ܢܙ O O O O O

I do not believe my dataframe is data. Here is my code so far.

Additional information: i need to join elements that say ch1a with the element right below it to read as part of the same column title. So the first row elements have to join together with the second row elements. please let me know if this still isn't clear

Answer 1

ANSWER:

• I have provided the properly commented code in both text and image format so you can easily copy the code as well as check for correct indentation.
• I have provided the input/output image of the code so you can easily cross-check for the correct output of the code.
• Have a nice and healthy day!!

CODE TEXT

import pandas as pd
import numpy as np

def ImportCustomScript(filename):
data=pd.read_csv(filename,sep='.',header=None)
# droping empty columns, using dropna method of pandas with axis=1
data=data.dropna(axis=1)
# concatenating first col and second column value if first value starts with ch
# using list comprehension to create list of concatenated values
# looping through each keys and fetch first and second value of col
# if first value start with ch concatenating first and second value
# otherwise returning first value
concatenated_values=[data[key][0]+data[key][1] if (data[key][0][:2] =='ch') else (data[key][0]) for key in data.keys()]
# replacing values of first column to concatenated_values
data.iloc[0] = concatenated_values
  
return data

ImportCustomScript('dataset.csv')

CODE IMAGE

4 7 1 import pandas as pd 2 import numpy as np 3 def ImportCustomScript(filename): 5 data=pd.read_csv(filename, sep='.', header=None) 6 # droping empty columns, using dropna method of pandas with axis=1 data-data.dropna(axis=1) # concatenating first col and second column value if first value starts with ch # using list comprehension to create list of concatenated values # Looping through each keys and fetch first and second value of col # if first value start with ch concatenating first and second value # otherwise returning first value concatenated_values=[data[key][0]+data[key][1] if (data[key][0][:2] =='ch') else (data[key][0]) for key in data.keys ()] # replacing values of first column to concatenated_values data.iloc[0] = concatenated_values 8 9 10 11 12. 13 14 15 16 17 return data 18 19 ImportCustomScript('dataset.csv')

INPUT IMAGE

D A B с 1 chla chla chla 2 isma::cas_ism _cmd_mode _cmd_model 3 single boolean uint32 4 11.42644024 0 0 5 11.42591953 0 o 6 11.4253931 0 E ch1b isma::cas_isr single 11.42644 11.42644 11.42539 0

OUTPUT IMAGE

o 1 2 4 Och1aisma: cas_ism ch1a_cmd_mode ch1a_cmd_mode1 ch1bisma: cas_isr isma cas_ism _cmd_mode _cmd_mode 1 isma cas_isr 2 single boolean uint32 single 1 3 11.42644024 0 0 11.42644 4 11.42591953 0 0 11.42644 5 11.4253931 0 0 11.42539