Moved update of q_name and q_number to routine

c66b10d8 · Moene, Arnold · 2ae78c0d · c66b10d8 · c66b10d8
Commit c66b10d8 authored 3 years ago by Moene, Arnold
--- a/programme_name_analysis.ipynb
+++ b/programme_name_analysis.ipynb
@@ -30,6 +30,7 @@
    "# Get the data from file\n",
    "fname='Survey name of programmes BSW & MEE(1-178).xlsx'\n",
    "df = pd.read_excel(fname)\n",
+    "df, q_number, q_name = extend_names(df, survey='students')\n",
    "\n",
    "# To show the short-hand names for the various columns: in q_names\n",
    "print(q_names.keys())"

 %% Cell type:markdown id: tags:
 # Analysis of survey about  name of current programmes BSW and MEE
 %% Cell type:code id: tags:
 ``` python
 import pandas as pd
 import matplotlib.pyplot as plt
 import numpy as np
 from toggle_cell import toggle_code as hide_code
 from survey_helpers import q_number, q_name, plot_pies, plot_bar, plot_ranking
 %matplotlib inline
 ```
 %% Cell type:code id: tags:
 ``` python
 # Get the data from file
 fname='Survey name of programmes BSW & MEE(1-178).xlsx'
 df = pd.read_excel(fname)
+df, q_number, q_name = extend_names(df, survey='students')
 # To show the short-hand names for the various columns: in q_names
 print(q_names.keys())
 ```
 %% Cell type:markdown id: tags:
 # Summary of population
 First we determine who filled out the survey
 * What is your current programme?
 * In which year of your programme are you?
 * As an student in MEE: did you study BSW before MEE
 %% Cell type:code id: tags:
 ``` python
 vars = ["curr_prog","year_BSW","year_in_MEE_total", "did_BSW"]
 plot_pies(vars)
 ```
 %% Cell type:markdown id: tags:
 # Preferred type of name
 Now let's look at the preferred type of name
 The study programmes BSW and MEE differ in composition from more standard programmes - for example, it is not common to combine meteorology and soil biology in one programme.
 * We can choose to emphasize this special composition in the name (a unique name). However, this may lead to a name that is not known in the Netherlands and abroad, which may reduce **recognizability** and **findability**. Which aspect do you find more important?
 * Names of study programmes can be either broad or specific. **Broad** names encompass all topics treated in the study programmes in a global manner and are typically short (the name is the ‘common denominator’). **Specific** names mention all disciplines separately and are typically longer. Which would you prefer?
 %% Cell type:code id: tags:
 ``` python
 # Which variables to look at
 vars = ["recgnize_unique","broad_specific"]
 # Split data by current programma and include the total number (and put 'neutral' nicely in the middle)
 plot_bar(df, 'curr_prog', vars, pref_middle='neutral')
 ```
 %% Cell type:markdown id: tags:
 # Ranking of various options within categories
 In the following three questions you have to rank possible names for our programme. The three questions differ in the way the alternative names are constructed. Based on your experience in BSW/MEE/BSW+MEE so far and your perception and feeling of the names, indicate which name summarizes the programme best. Put the names in order of your preference with your most preferred on top. This enumeration are based on:
 * synonyms
 * names with 'environment'
 * names with 'earth'
 %% Cell type:code id: tags:
 ``` python
 # Which rankings to look at
 orders = ['order_synonym', 'order_environment', 'order_earth']
 # Split data by current programma and include the total number
 plot_ranking(df, 'curr_prog', orders, include_all=True)
 ```
 %% Cell type:markdown id: tags:
 And which of the orderings did you prefer?
 %% Cell type:code id: tags:
 ``` python
 # Which rankings to look at
 orders = ['which_order']
 # Split data by current programma, include the total number and put the graphs next to each other
 plot_ranking(df, 'curr_prog', orders, include_all=True, transpose=True)
 ```
 %% Cell type:markdown id: tags:
 ## Prefixes?
 The previous names for the programme did not entail any of the prefixes mentioned below. Do you think that any of the following prefixes would have an added value?
 %% Cell type:code id: tags:
 ``` python
 # Which variables to look at
 vars = ["prefix"]
 # Split data by current programma, include the total numbe
 plot_bar(df, 'curr_prog', vars, include_all=True)
 ```
 %% Cell type:code id: tags:
 ``` python
 ```

--- a/survey_helpers.py
+++ b/survey_helpers.py
@@ -183,12 +183,15 @@ def plot_ranking(mydf, split_by, orders, include_all = True, transpose=False):
            plt.xlabel('fraction of respondents')
            plt.tight_layout()
            plt.title('%s: %s'%(q_name[split_by],prog))
-df, q_number, q_name = combine_cols(df, 'year_MEE', 'year_MEE2', 'year_in_MEE_total', 
+def extend_names(mydf, survey='students'):
+    if (survey == 'students'):    
+    	mydf, q_number, q_name = combine_cols(mydf, 'year_MEE', 'year_MEE2', 'year_in_MEE_total', 
                                    q_number, q_name, 'Year in MEE')
-df, q_number, q_name = combine_cols(df, 'attract_name_MEE', 'attract_name_MEE2', 'attract_name_MEE_total', 
+    	mydf, q_number, q_name = combine_cols(mydf, 'attract_name_MEE', 'attract_name_MEE2', 'attract_name_MEE_total', 
                                    q_number, q_name, 'Attractive in name MEE')
-df, q_number, q_name = combine_cols(df, 'miss_name_BSW', 'miss_name_BSW2', 'miss_name_BSW_total', 
+    	mydf, q_number, q_name = combine_cols(mydf, 'miss_name_BSW', 'miss_name_BSW2', 'miss_name_BSW_total', 
                                    q_number, q_name, 'Missed in name BSW')
-df, q_number, q_name = combine_cols(df, 'miss_name_MEE', 'miss_name_MEE2', 'miss_name_MEE_total', 
+    	mydf, q_number, q_name = combine_cols(mydf, 'miss_name_MEE', 'miss_name_MEE2', 'miss_name_MEE_total', 
                                    q_number, q_name, 'Missed in name MEE')
+     return (mydf, q_number, q_name)