回答編集履歴
2
適切に連番でRankが振られるように修正
test
CHANGED
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@@ -6,7 +6,13 @@
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6
6
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7
7
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df = pd.read_csv('test.csv')
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8
8
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9
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-
df2 = df.groupby('COUNTRY_NAME').size().rank(
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9
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+
df2 = df.groupby('COUNTRY_NAME').size().rank(
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10
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+
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11
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+
ascending=False,
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12
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+
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13
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+
method='first'
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14
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+
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15
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+
).astype(int).reset_index(name='RANK')
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10
16
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11
17
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df = df.merge(df2, right_index=True, on='COUNTRY_NAME').sort()
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12
18
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@@ -20,8 +26,6 @@
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20
26
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21
27
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```
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22
28
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23
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-
GENDER AGE STATUS COUNTRY_NAME
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24
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-
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25
29
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0 F 41 NeverM USA
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26
30
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27
31
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1 M 30 NeverM Brazil
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@@ -34,6 +38,10 @@
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34
38
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35
39
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5 M 40 NeverM USA
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36
40
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41
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+
6 M 40 NeverM China
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42
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+
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43
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+
7 F 21 Married China
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44
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+
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37
45
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```
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38
46
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39
47
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@@ -44,16 +52,20 @@
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44
52
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45
53
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GENDER AGE STATUS COUNTRY_NAME RANK
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46
54
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47
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-
0 F 41 NeverM USA 1
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55
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+
0 F 41 NeverM USA 1
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48
56
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49
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-
1 M 30 NeverM Brazil
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57
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+
1 M 30 NeverM Brazil 4
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50
58
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51
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-
2 F 21 Married USA 1
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59
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+
2 F 21 Married USA 1
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52
60
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53
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-
3 M 40 NeverM Japan
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61
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+
3 M 40 NeverM Japan 3
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54
62
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55
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-
4 F 21 Married Japan
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63
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+
4 F 21 Married Japan 3
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56
64
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57
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-
5 M 40 NeverM USA 1
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65
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+
5 M 40 NeverM USA 1
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66
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+
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67
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+
6 M 40 NeverM China 2
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68
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+
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69
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+
7 F 21 Married China 2
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58
70
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59
71
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```
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1
元の並び順を維持するようにしました。
test
CHANGED
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@@ -8,7 +8,7 @@
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8
8
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9
9
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df2 = df.groupby('COUNTRY_NAME').size().rank(ascending=False).reset_index(name='RANK')
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10
10
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11
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-
df = df.merge(df2, on='COUNTRY_NAME')
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11
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+
df = df.merge(df2, right_index=True, on='COUNTRY_NAME').sort()
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12
12
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13
13
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```
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14
14
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@@ -46,14 +46,14 @@
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46
46
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47
47
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0 F 41 NeverM USA 1.0
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48
48
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49
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-
1
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49
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+
1 M 30 NeverM Brazil 3.0
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50
50
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51
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-
2
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51
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+
2 F 21 Married USA 1.0
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52
52
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53
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-
3 M
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53
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+
3 M 40 NeverM Japan 2.0
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54
54
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55
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-
4
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55
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+
4 F 21 Married Japan 2.0
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56
56
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57
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-
5
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57
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+
5 M 40 NeverM USA 1.0
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58
58
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59
59
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```
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