示例#1
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Spyder Editor

This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

# Read DE16 data
de16 = de.read_sparta_survey(7)
de16_meta = de.meta(7)

# CR_DEVCNT2 for DE16
cr_devcnt2_16 = de.dist(de16, de16_meta, 'CR_DEVCNT2', 'WghtUniversal_Core')
cr_devcnt2_16.to_clipboard()

# Professionals - what do you think?
# Filter on any dev who is professional in at least one sector

de16['Prof'] = (de16[[
    'CR2b_1_1', 'CR2b_2_1', 'CR2b_3_1', 'CR2b_4_1', 'CR2b_5_1', 'CR2b_6_1',
    'CR2b_7_1', 'CR2b_8_1', 'CR2b_9_1', 'CR2b_10_1'
]].any(axis=1)).astype(float).replace(0, 2)

pros_only = de.dist(de16[de16.Prof == 1], de16_meta, 'CR_DEVCNT2',
                    'WghtUniversal_Core')
示例#2
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This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

##################
# Read DE16 data
de16 = de.read_sparta_survey(7)
de16_meta = de.meta(7)


##################

#Crosstab all devs geographical regions against development area
regions=de.crosstab(de16, de16_meta, 'RegionCode8','CR2a', 'WghtUniversal_Core')
regions.to_clipboard()

#Crosstab professionals only in geographical regions against development area
de16['Prof']  = (de16[['CR2b_2_1']].any(axis=1)).astype(float).replace(0,2)
regions=de.crosstab(de16[de16.Prof==1], de16_meta, 'RegionCode8','CR2a', 'WghtUniversal_Core')
regions.to_clipboard()


mob_devs = (de16.CR2a_2==1)
示例#3
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This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

# Read DE15 data
de15 = de.read_sparta_survey(6)
de15_meta = de.meta(6)

# Read DE14 data
de14 = de.read_sparta_survey(5)
de14_meta = de.meta(5)

# Read DE13 data
de13 = de.read_sparta_survey(4)
de13_meta = de.meta(4)

#GAM1: What types of platform do you develop games for?
gam1 = de.dist(de15, de15_meta, 'GAM1', 'WghtUniversal_Game')
gam1pc = de.calc_pct(gam1)
gam1pc.to_clipboard()

#GAM1
示例#4
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This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

##################
# Read de14 data
de14 = de.read_sparta_survey(5)
de14_meta = de.meta(5)
##################

#Non professionals
de14['nonprof'] = (de14[['CR2_2_2',
                         'CR2_2_3']].any(axis=1)).astype(float).replace(0, 2)
npros_only = de.dist(de14[de14.nonprof == 1], de14_meta, 'MOB4',
                     'WghtUniversal_Mob')
npros_onlypc = de.calc_pct(npros_only)
npros_onlypc.to_clipboard()

# Mobile professionals only
de14['Prof'] = (de14[['CR2_2_1']].any(axis=1)).astype(float).replace(0, 2)
pros_only = de.dist(de14[de14.Prof == 1], de14_meta, 'MOB4',
                    'WghtUniversal_Core')
pros_onlypc = de.calc_pct(pros_only)
示例#5
0
This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

##################
# Read de15 data
de15 = de.read_sparta_survey(6)
de15_meta = de.meta(6)

##################
#Non professionals
de15['nonprof'] = (de15[['CR2_2_2',
                         'CR2_2_3']].any(axis=1)).astype(float).replace(0, 2)
npros_only = de.dist(de15[de15.nonprof == 1], de15_meta, 'MOB2',
                     'WghtUniversal_Mob')
npros_onlypc = de.calc_pct(npros_only)
npros_onlypc.to_clipboard()

# Mobile professionals only
de15['Prof'] = (de15[['CR2_2_1']].any(axis=1)).astype(float).replace(0, 2)
pros_only = de.dist(de15[de15.Prof == 1], de15_meta, 'MOB_POP2',
                    'WghtUniversal_Core')
pros_onlypc = de.calc_pct(pros_only)
示例#6
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"""



# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

##################
# Read de13 data
de13 = de.read_sparta_survey(4)
de13_meta = de.meta(4)
##################


#MOB3: What programming languages?
mob3 = de.dist(de13, de13_meta, 'MOB3', 'WghtUniversal_Mob')
mob3pc = de.calc_pct(mob3)
mob3pc.to_clipboard()

# Mobile professionals only
de13['Prof']  = (de13[['CR2_2_1']].any(axis=1)).astype(float).replace(0,2)
pros_only = de.dist(de13[de13.Prof==1], de13_meta, 'MOB3', 'WghtUniversal_Core')
pros_onlypc = de.calc_pct(pros_only)
pros_onlypc.to_clipboard()

#Filter mobile devs programming language choice by those that use cross platform dev tools
示例#7
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Granny-Clanger:~ stichbury$ /Users/stichbury/anaconda/envs/py3/bin/spyder ; exit;

@author: stichbury
"""

# -*- coding: utf-8 -*-
"""
Spyder Editor

This is a temporary script file.
"""

# Imports
import pandas as pd
import deutils as de
import numpy as np

# weights
Sparta_Core = 'WghtUniversal_Core'

##################
# Read de14 data
de12 = de.read_sparta_survey(3)
de12_meta = de.meta(3)
##################

# CR6: experience levels over survey
cr6 = de.dist(de12, de12_meta, 'CR6', 'WghtUniversal_Core')
cr6_pc = de.calc_pct(cr6, pct_type='row')
cr6_pc.to_clipboard()