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12 processed data files; 1 sql instructions file #10

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998a174
12 processed data files; 1 sql instructions file
hujambo-dunia Aug 25, 2022
15e7c30
column name adjustment in Total Memory data file
hujambo-dunia Aug 25, 2022
0ef0367
column name adjustment in Total Memory data file
hujambo-dunia Aug 25, 2022
76f16d7
fix for data file missing column name
hujambo-dunia Aug 26, 2022
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18,124 changes: 18,124 additions & 0 deletions data/2022/avg_cpu_time_all.csv
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13 changes: 13 additions & 0 deletions data/2022/avg_cpu_time_all_inverted.csv
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322 changes: 161 additions & 161 deletions data/2022/avgmemory_all.csv
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2 changes: 1 addition & 1 deletion data/2022/avgmemory_all_inverted.csv
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18,124 changes: 18,124 additions & 0 deletions data/2022/total_cpu_time_all.csv
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13 changes: 13 additions & 0 deletions data/2022/total_cpu_time_all_inverted.csv
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18,124 changes: 18,124 additions & 0 deletions data/2022/total_cpu_time_numjobs.csv
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822 changes: 411 additions & 411 deletions data/2022/totalmemory_all.csv
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2 changes: 1 addition & 1 deletion data/2022/totalmemory_all_inverted.csv
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750 changes: 375 additions & 375 deletions data/2022/totalmemory_numjobs.csv
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64 changes: 32 additions & 32 deletions data/inverted_processed_result.py
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import pandas as pd

### invert the numusers_all csv file
numusers_all = pd.read_csv('./numusers_all.csv',names = ['month_year','num_users','tool_name_version'],skiprows = 1)
# ### invert the numusers_all csv file
numusers_all = pd.read_csv('2022_new/STEP_3_0_clean_data/numusers_all.csv',names = ['month_year','num_users','tool_name_version'],skiprows = 1)
numusers_all = numusers_all.drop_duplicates(['month_year','tool_name_version'])
numusers_all_inverted = numusers_all.pivot(index='month_year', columns='tool_name_version', values='num_users')
numusers_all_inverted = numusers_all_inverted.fillna(0)
numusers_all_inverted.to_csv('numusers_all_inverted.csv')
numusers_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/numusers_all_inverted.csv')

### invert the numjobs_all csv file
numjobs_all = pd.read_csv('./numjobs_all.csv',names = ['month_year','num_jobs','tool_name_version'],skiprows = 1)
numjobs_all = numjobs_all.drop_duplicates(['month_year','tool_name_version'])
numjobs_all_inverted = numjobs_all.pivot(index='month_year', columns='tool_name_version', values='num_jobs')
numjobs_all_inverted = numjobs_all_inverted.fillna(0)
numjobs_all_inverted.to_csv('numjobs_all_inverted.csv')
# ### invert the numjobs_all csv file
# numjobs_all = pd.read_csv('2022_new/STEP_3_0_clean_data/numjobs_all.csv',names = ['month_year','num_jobs','tool_name_version'],skiprows = 1)
# numjobs_all = numjobs_all.drop_duplicates(['month_year','tool_name_version'])
# numjobs_all_inverted = numjobs_all.pivot(index='month_year', columns='tool_name_version', values='num_jobs')
# numjobs_all_inverted = numjobs_all_inverted.fillna(0)
# numjobs_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/numjobs_all_inverted.csv')

### invert the total_cpu_time_all csv file
total_cpu_time_all = pd.read_csv('./total_cpu_time_all.csv',names = ['month_year','total_cpu_time','tool_name_version'],skiprows = 1)
total_cpu_time_all = total_cpu_time_all.drop_duplicates(['month_year','tool_name_version'])
total_cpu_time_all_inverted = total_cpu_time_all.pivot(index='month_year', columns='tool_name_version', values='total_cpu_time')
total_cpu_time_all_inverted = total_cpu_time_all_inverted.fillna(0)
total_cpu_time_all_inverted.to_csv('total_cpu_time_all_inverted.csv')
# ### invert the total_cpu_time_all csv file
# total_cpu_time_all = pd.read_csv('2022_new/STEP_3_0_clean_data/total_cpu_time_all.csv',names = ['month_year','total_cpu_time','tool_name_version'],skiprows = 1)
# total_cpu_time_all = total_cpu_time_all.drop_duplicates(['month_year','tool_name_version'])
# total_cpu_time_all_inverted = total_cpu_time_all.pivot(index='month_year', columns='tool_name_version', values='total_cpu_time')
# total_cpu_time_all_inverted = total_cpu_time_all_inverted.fillna(0)
# total_cpu_time_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/total_cpu_time_all_inverted.csv')

### invert the totalmemory_all csv file
totalmemory_all = pd.read_csv('./totalmemory_all.csv',names = ['month_year','totalmemory','tool_name_version'],skiprows = 1)
totalmemory_all = totalmemory_all.drop_duplicates(['month_year','tool_name_version'])
totalmemory_all_inverted = totalmemory_all.pivot(index='month_year', columns='tool_name_version', values='totalmemory')
totalmemory_all_inverted = totalmemory_all_inverted.fillna(0)
totalmemory_all_inverted.to_csv('totalmemory_all_inverted.csv')
# ### invert the totalmemory_all csv file
# totalmemory_all = pd.read_csv('2022_new/STEP_3_0_clean_data/totalmemory_all.csv',names = ['month_year','totalmemory','tool_name_version'],skiprows = 1)
# totalmemory_all = totalmemory_all.drop_duplicates(['month_year','tool_name_version'])
# totalmemory_all_inverted = totalmemory_all.pivot(index='month_year', columns='tool_name_version', values='totalmemory')
# totalmemory_all_inverted = totalmemory_all_inverted.fillna(0)
# totalmemory_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/totalmemory_all_inverted.csv')

### invert the avg_cpu_time_all csv file
avg_cpu_time_all = pd.read_csv('./avg_cpu_time_all.csv',names = ['month_year','avg_cpu_time','tool_name_version'],skiprows = 1)
avg_cpu_time_all = avg_cpu_time_all.drop_duplicates(['month_year','tool_name_version'])
avg_cpu_time_all_inverted = avg_cpu_time_all.pivot(index='month_year', columns='tool_name_version', values='avg_cpu_time')
avg_cpu_time_all_inverted = avg_cpu_time_all_inverted.fillna(0)
avg_cpu_time_all_inverted.to_csv('avg_cpu_time_all_inverted.csv')
# avg_cpu_time_all = pd.read_csv('2022_new/STEP_3_0_clean_data/avg_cpu_time_all.csv',names = ['month_year','avg_cpu_time','tool_name_version'],skiprows = 1)
# avg_cpu_time_all = avg_cpu_time_all.drop_duplicates(['month_year','tool_name_version'])
# avg_cpu_time_all_inverted = avg_cpu_time_all.pivot(index='month_year', columns='tool_name_version', values='avg_cpu_time')
# avg_cpu_time_all_inverted = avg_cpu_time_all_inverted.fillna(0)
# avg_cpu_time_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/avg_cpu_time_all_inverted.csv')

### invert the avgmemory_all csv file
avgmemory_all = pd.read_csv('./avg_memory_all.csv',names = ['month_year','avgmemory','tool_name_version'],skiprows = 1)
avgmemory_all = avgmemory_all.drop_duplicates(['month_year','tool_name_version'])
avgmemory_all_inverted = avgmemory_all.pivot(index='month_year', columns='tool_name_version', values='avgmemory')
avgmemory_all_inverted = avgmemory_all_inverted.fillna(0)
avgmemory_all_inverted.to_csv('avgmemory_all_inverted.csv')
# ### invert the avgmemory_all csv file
# avgmemory_all = pd.read_csv('2022_new/STEP_3_0_clean_data/avg_memory_all.csv',names = ['month_year','avgmemory','tool_name_version'],skiprows = 1)
# avgmemory_all = avgmemory_all.drop_duplicates(['month_year','tool_name_version'])
# avgmemory_all_inverted = avgmemory_all.pivot(index='month_year', columns='tool_name_version', values='avgmemory')
# avgmemory_all_inverted = avgmemory_all_inverted.fillna(0)
# avgmemory_all_inverted.to_csv('2022_new/STEP_3_1_chart_views/avgmemory_all_inverted.csv')
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