ejcer

given an array of size n in which every number is between 1 and n, determine if there are any duplicates.

ask dumb questions:
are they ints, is it sorted, are there any restrictions. Can you use additional space. Can it be empty.

go with brute force question (make sure it's rock solid)

ejcer

/*Checks 4 cases:
 * when no argument is supplied & there are no stopped jobs
 * when no argument is supplied & there is a stopped job
 * when an argument is supplied & there is no stopped job at that jid or the argument is junk
 * when an argument is supplied & there is a stopped job at that jid */
void
execute_bg_command()
{
  struct list_elem *eJob = list_rbegin(&job_list);
  struct esh_pipeline * lastJob = list_entry(eJob, struct esh_pipeline, elem);

ejcer

bool
execute_plugin(struct esh_command * cmd)
{
  struct list_elem * e = list_begin(&esh_plugin_list);
  
  for (; e != list_end(&esh_plugin_list); e = list_next (e)){
    struct esh_plugin * currPlugin = list_entry(e, struct esh_plugin, elem);
    
    if(currPlugin->process_builtin == NULL){
	  continue;

ejcer

#Fit a linear regression line to model IncomePerCapita 'y' as a function of
#PercentCollegeGrad 'x' from the states.csv data set.

### Imports ###
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import os
os.chdir('/home/edward/workspace/school/datavis')
os.getcwd()

ejcer

28                  Nevada
30              New Jersey
6              Connecticut
32                New York
38            Pennsylvania
22                Michigan
13                Illinois
14                 Indiana
11                  Hawaii
9                  Florida

ejcer

# Gather some data that is of interest to you.
# Analyze the data using a scatterplot matrix. List at least 3 non-trivial
#findings about the data, along with plot pictures that show the findings.


### Imports ###
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import os

ejcer

#class survey data surveyV01.csv
#Use Pandas to clean all the problems you can find in the data and write a
#single clean surveyCleaned_LastName.csv file.

#Submit a list of all the types of problems you found, and for each problem
#show the Python code you used to fix it, in the textbox.


### Imports ###
import numpy as np

ejcer

# Gather some data that is of interest to you.
# Analyze the data using a scatterplot matrix. List at least 3 non-trivial
#findings about the data, along with plot pictures that show the findings.


### Imports ###
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import os

ejcer

def main():
    PF1 = "124*+3-22+-3/2/3*"
    PF2 = "65-4*54/7*+9-9-"
    global tos
    tos = -1

    def push(s, elem):
        global tos
        tos = 1+tos

ejcer

              5
        /            \
        2             6
    /      \
    1       3
             \
              4