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Complex Experimental Design - Qualtrics Wide to Long Melt Example
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Qualtrics.SurveyEngine.addOnload(function() | |
{ | |
jQuery('#QID1013 input.radio').prop( "checked", true ); | |
jQuery(document).ready(function(){ | |
jQuery('#QID1013 input.radio').prop( "checked", true ); | |
}) | |
}); |
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# -*- coding: utf-8 -*- | |
""" | |
Created on Sun Jan 25 10:03:56 2017 | |
@author: Robin van Emden [robin@pwy.nl] | |
""" | |
# pandas: imports our CSV and manipulates DataFrame df | |
# re: enables the use of regular expressions to selectively replace values | |
import pandas | |
import re | |
# string join function, with "##" as the seperator | |
def sjoin(x): return '##'.join(x[x.notnull()].astype(str)) | |
# load the CSV into a dataframe, exclude header discription | |
df = pandas.read_csv("data.csv",low_memory=False,skiprows=[1]); | |
# load the two CSV header rows into a dataframe | |
df_header = pandas.read_csv("data.csv",nrows=2); | |
# remove the parentheses from the column names | |
df = df.rename(columns=lambda x: re.sub(r"\(.*\)","",x)) | |
df_header = df_header.rename(columns=lambda x: re.sub(r"\(.*\)","",x)) | |
# merge the columns that have the same name | |
df = df.groupby(level=0, axis=1).apply(lambda x: x.apply(sjoin, axis=1)) | |
df_header = df_header.groupby(level=0, axis=1).apply(lambda x: x.apply(sjoin, axis=1)) | |
# remove duplicate descriptions from second row (column descriptions) | |
#df.iloc[:1] = df.iloc[:1].replace({'##.*': ''}, regex=True) | |
df_header.iloc[:1] = df_header.iloc[:1].replace({'##.*': ''}, regex=True) | |
# cleaning up leftover parentheses in second row (column descriptions) | |
#df.iloc[:1] = df.iloc[:1].replace({'\(.*\)': ''}, regex=True) | |
df_header.iloc[:1] = df_header.iloc[:1].replace({'\(.*\)': ''}, regex=True) | |
# lets split C1 to C6 to make them easier to parse later on | |
for i in range(1, 7): | |
df['C'+str(i)+'_lbl'], df['C'+str(i)+'_img'] = df['C'+str(i)].str.split('/', 1).str | |
for i in range(1, 7): | |
df_header['C'+str(i)+'_lbl'], df_header['C'+str(i)+'_img'] = df_header['C'+str(i)].str.split('/', 1).str | |
# do some reordering to move the condition values to the front | |
tofront = ['C1_lbl','C1_img','C2_lbl','C2_img','C3_lbl','C3_img','C4_lbl','C4_img','C5_lbl','C5_img','C6_lbl','C6_img','RAND_LABELS','RAND_IMG_1_TEXT','RAND_IMG_2_TEXT','RAND_IMG_3_TEXT','RAND_IMG_4_TEXT','RAND_IMG_5_TEXT', 'RAND_IMG_6_TEXT','RAND_LABEL'] | |
df = df[ [c for c in tofront if c in df] + [c for c in df if c not in tofront]] | |
tofront = ['C1_lbl','C1_img','C2_lbl','C2_img','C3_lbl','C3_img','C4_lbl','C4_img','C5_lbl','C5_img','C6_lbl','C6_img','RAND_LABELS','RAND_IMG_1_TEXT','RAND_IMG_2_TEXT','RAND_IMG_3_TEXT','RAND_IMG_4_TEXT','RAND_IMG_5_TEXT', 'RAND_IMG_6_TEXT','RAND_LABEL'] | |
df_header = df_header[ [c for c in tofront if c in df] + [c for c in df if c not in tofront]] | |
df_header = df_header.fillna('') | |
df_header = df_header[:1] | |
filename = "data__MELTED.csv"; | |
df_header.to_csv(filename,float_format='%.6f'); | |
with open(filename, 'a') as f: | |
df.to_csv(f,header=False,float_format='%.6f'); |
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String.prototype.shuffle = function () { | |
var a = this.split(""), | |
n = a.length; | |
for(var i = n - 1; i > 0; i--) { | |
var j = Math.floor(Math.random() * (i + 1)); | |
var tmp = a[i]; | |
a[i] = a[j]; | |
a[j] = tmp; | |
} | |
return a.join(""); | |
} | |
var reorder = "123456".shuffle() | |
Qualtrics.SurveyEngine.addOnload(function() | |
{ | |
jQuery('#QID1013 input.radio').prop( "checked", true ); | |
jQuery(document).ready(function(){ | |
jQuery('#QID1013 input.radio').prop( "checked", true ); | |
}) | |
jQuery('#QID1019 .InputText').eq(0).val(reorder.charAt(0)); | |
jQuery('#QID1019 .InputText').eq(1).val(reorder.charAt(1)); | |
jQuery('#QID1019 .InputText').eq(2).val(reorder.charAt(2)); | |
jQuery('#QID1019 .InputText').eq(3).val(reorder.charAt(3)); | |
jQuery('#QID1019 .InputText').eq(4).val(reorder.charAt(4)); | |
jQuery('#QID1019 .InputText').eq(5).val(reorder.charAt(5)); | |
}); |
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