In [49]:
import pandas as pd
from pandas.io.excel import ExcelFile
In [50]:
infile = ExcelFile('ColorBrewer_all_schemes_RGBonly3.XLS')
In [51]:
df = infile.parse(infile.sheet_names[0])
In [52]:
df_fill = df.fillna(method = 'ffill')
In [53]:
df_fill.head()
Out[53]:
ColorName
NumOfColors
Type
CritVal
ColorNum
ColorLetter
R
G
B
SchemeType
0
Accent
3
qual
NaN
1
A
127
201
127
Qualitative
1
Accent
3
qual
NaN
2
B
190
174
212
Qualitative
2
Accent
3
qual
NaN
3
C
253
192
134
Qualitative
3
Accent
4
qual
NaN
1
A
127
201
127
Qualitative
4
Accent
4
qual
NaN
2
B
190
174
212
Qualitative
In [54]:
df_fill = df_fill.drop(['Type', 'ColorLetter'], axis = 1)
In [55]:
df_fill.head()
Out[55]:
ColorName
NumOfColors
CritVal
ColorNum
R
G
B
SchemeType
0
Accent
3
NaN
1
127
201
127
Qualitative
1
Accent
3
NaN
2
190
174
212
Qualitative
2
Accent
3
NaN
3
253
192
134
Qualitative
3
Accent
4
NaN
1
127
201
127
Qualitative
4
Accent
4
NaN
2
190
174
212
Qualitative
In [56]:
#df_key = pd.factorize(pd.lib.fast_zip([df_fill.ColorName, df_fill.NumOfColors]))
In [57]:
#df_key[0]
In [58]:
#df_fill.index = df_key[0]
In [59]:
df_fill.head(40)
Out[59]:
ColorName
NumOfColors
CritVal
ColorNum
R
G
B
SchemeType
0
Accent
3
NaN
1
127
201
127
Qualitative
1
Accent
3
NaN
2
190
174
212
Qualitative
2
Accent
3
NaN
3
253
192
134
Qualitative
3
Accent
4
NaN
1
127
201
127
Qualitative
4
Accent
4
NaN
2
190
174
212
Qualitative
5
Accent
4
NaN
3
253
192
134
Qualitative
6
Accent
4
NaN
4
255
255
153
Qualitative
7
Accent
5
NaN
1
127
201
127
Qualitative
8
Accent
5
NaN
2
190
174
212
Qualitative
9
Accent
5
NaN
3
253
192
134
Qualitative
10
Accent
5
NaN
4
255
255
153
Qualitative
11
Accent
5
NaN
5
56
108
176
Qualitative
12
Accent
6
NaN
1
127
201
127
Qualitative
13
Accent
6
NaN
2
190
174
212
Qualitative
14
Accent
6
NaN
3
253
192
134
Qualitative
15
Accent
6
NaN
4
255
255
153
Qualitative
16
Accent
6
NaN
5
56
108
176
Qualitative
17
Accent
6
NaN
6
240
2
127
Qualitative
18
Accent
7
NaN
1
127
201
127
Qualitative
19
Accent
7
NaN
2
190
174
212
Qualitative
20
Accent
7
NaN
3
253
192
134
Qualitative
21
Accent
7
NaN
4
255
255
153
Qualitative
22
Accent
7
NaN
5
56
108
176
Qualitative
23
Accent
7
NaN
6
240
2
127
Qualitative
24
Accent
7
NaN
7
191
91
23
Qualitative
25
Accent
8
NaN
1
127
201
127
Qualitative
26
Accent
8
NaN
2
190
174
212
Qualitative
27
Accent
8
NaN
3
253
192
134
Qualitative
28
Accent
8
NaN
4
255
255
153
Qualitative
29
Accent
8
NaN
5
56
108
176
Qualitative
30
Accent
8
NaN
6
240
2
127
Qualitative
31
Accent
8
NaN
7
191
91
23
Qualitative
32
Accent
8
NaN
8
102
102
102
Qualitative
33
Blues
3
NaN
1
222
235
247
Sequential
34
Blues
3
NaN
2
158
202
225
Sequential
35
Blues
3
NaN
3
49
130
189
Sequential
36
Blues
4
NaN
1
239
243
255
Sequential
37
Blues
4
NaN
2
189
215
231
Sequential
38
Blues
4
NaN
3
107
174
214
Sequential
39
Blues
4
NaN
4
33
113
181
Sequential
In [60]:
df_fill.to_excel('ColorBrewer_all_schemes_RGBonly3_updated.XLS', sheet_name = 'Sheet1')
In [61]:
df_fill.to_csv('ColorBrewer_all_schemes_RGBonly3_updated.csv', header = False)
In [65]:
test_in = pd.read_csv('ColorBrewer_all_schemes_RGBonly3_updated.csv')
In [66]:
test_in.head()
Out[66]:
0
Accent
3.0
Unnamed: 3
1.0
127.0
201.0
127.0.1
Qualitative
0
1
Accent
3
NaN
2
190
174
212
Qualitative
1
2
Accent
3
NaN
3
253
192
134
Qualitative
2
3
Accent
4
NaN
1
127
201
127
Qualitative
3
4
Accent
4
NaN
2
190
174
212
Qualitative
4
5
Accent
4
NaN
3
253
192
134
Qualitative
Out[66]:
0
Accent
3.0
Unnamed: 3
1.0
127.0
201.0
127.0.1
Qualitative
0
1
Accent
3
NaN
2
190
174
212
Qualitative
1
2
Accent
3
NaN
3
253
192
134
Qualitative
2
3
Accent
4
NaN
1
127
201
127
Qualitative
3
4
Accent
4
NaN
2
190
174
212
Qualitative
4
5
Accent
4
NaN
3
253
192
134
Qualitative
Out[66]:
0
Accent
3.0
Unnamed: 3
1.0
127.0
201.0
127.0.1
Qualitative
0
1
Accent
3
NaN
2
190
174
212
Qualitative
1
2
Accent
3
NaN
3
253
192
134
Qualitative
2
3
Accent
4
NaN
1
127
201
127
Qualitative
3
4
Accent
4
NaN
2
190
174
212
Qualitative
4
5
Accent
4
NaN
3
253
192
134
Qualitative
In [ ]:
Content source: cmgerber/CensusMapper
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