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質問するログイン新規登録
トップPythonに関する質問特定の値がデータフレーム内の各カラム内にいくつ存在しているか数える方法。

編集履歴

回答編集履歴

1

表示失敗を修正

2021/06/04 10:52

投稿

ppaul
ppaul

スコア24670

test CHANGED
@@ -12,101 +12,101 @@
12
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  dates
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- 2021-04-29 1 2 0 0 0
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+ 2021-04-29 0 0 0 0 0
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  2021-04-30 1 0 0 0 0
18
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19
- 2021-05-01 0 2 1 0 0
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-
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- 2021-05-02 1 0 1 0 1
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-
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- 2021-05-03 2 0 1 0 0
24
-
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- 2021-05-04 0 0 1 2 1
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-
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- 2021-05-05 0 0 0 0 0
28
-
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- 2021-05-06 1 0 2 1 0
30
-
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- 2021-05-07 1 1 0 0 1
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-
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- 2021-05-08 0 2 1 0 0
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-
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- 2021-05-11 0 1 0 0 1
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-
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- 2021-05-12 0 3 0 1 2
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-
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- 2021-05-13 1 2 0 0 3
40
-
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- 2021-05-14 5 2 0 0 1
42
-
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- 2021-05-15 1 1 1 0 3
44
-
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- 2021-05-16 1 2 1 4 1
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-
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- 2021-05-17 1 2 0 5 1
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-
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- 2021-05-18 1 0 1 1 0
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-
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- 2021-05-19 0 1 2 1 0
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-
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- 2021-05-20 0 0 1 4 1
54
-
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- 2021-05-21 1 1 1 1 2
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-
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- 2021-05-22 0 1 5 0 0
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-
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- 2021-05-23 2 2 1 0 2
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-
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- 2021-05-24 2 1 1 1 1
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-
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- 2021-05-25 2 1 0 1 0
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-
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- 2021-05-26 0 0 0 2 0
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-
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- 2021-05-27 1 1 0 1 1
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-
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- 2021-05-28 0 0 1 0 1
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-
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- 2021-05-29 0 0 0 0 0
72
-
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- 2021-05-30 1 0 1 1 1
74
-
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- 2021-05-31 0 1 0 2 1
76
-
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- 2021-06-01 0 0 2 0 0
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-
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- 2021-06-02 1 1 0 0 0
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-
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- 2021-06-03 3 0 0 1 1
82
-
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- 2021-06-04 0 0 1 1 0
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-
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- 2021-05-12 0 3 0 1 2
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-
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- 2021-05-13 1 2 0 0 3
88
-
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- 2021-05-14 5 2 0 0 1
90
-
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- 2021-05-15 1 1 1 0 3
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-
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- 2021-05-16 1 2 1 4 1
94
-
95
- 2021-05-17 1 2 0 5 1
96
-
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- 2021-05-18 1 0 1 1 0
98
-
99
- 2021-05-19 0 1 2 1 0
100
-
101
- 2021-05-20 0 0 1 4 1
102
-
103
- 2021-05-21 1 1 1 1 2
104
-
105
- 2021-05-22 0 1 5 0 0
106
-
107
- 2021-05-23 2 2 1 0 2
108
-
109
- 2021-05-24 2 1 1 1 1
19
+ 2021-05-01 1 0 0 0 1
20
+
21
+ 2021-05-02 0 0 0 0 0
22
+
23
+ 2021-05-03 1 0 0 2 0
24
+
25
+ 2021-05-04 0 0 0 0 0
26
+
27
+ 2021-05-05 1 0 0 0 1
28
+
29
+ 2021-05-06 2 0 1 0 0
30
+
31
+ 2021-05-07 0 0 0 0 0
32
+
33
+ 2021-05-08 0 1 0 0 0
34
+
35
+ 2021-05-11 0 3 1 1 1
36
+
37
+ 2021-05-12 1 1 1 0 2
38
+
39
+ 2021-05-13 0 0 1 0 0
40
+
41
+ 2021-05-14 1 0 0 1 2
42
+
43
+ 2021-05-15 3 1 1 3 0
44
+
45
+ 2021-05-16 0 2 0 0 0
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+
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+ 2021-05-17 0 1 0 2 0
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+
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+ 2021-05-18 1 0 2 2 3
50
+
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+ 2021-05-19 0 1 0 0 0
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+
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+ 2021-05-20 2 2 0 0 2
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+
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+ 2021-05-21 0 0 0 0 0
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+
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+ 2021-05-22 0 2 2 2 0
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+
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+ 2021-05-23 0 0 1 2 1
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+
61
+ 2021-05-24 0 0 1 0 1
62
+
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+ 2021-05-25 0 0 0 1 1
64
+
65
+ 2021-05-26 1 0 0 0 1
66
+
67
+ 2021-05-27 1 0 1 0 0
68
+
69
+ 2021-05-28 1 0 0 0 0
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+
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+ 2021-05-29 0 1 0 0 0
72
+
73
+ 2021-05-30 1 0 1 0 0
74
+
75
+ 2021-05-31 0 2 0 0 0
76
+
77
+ 2021-06-01 0 1 1 1 1
78
+
79
+ 2021-06-02 1 1 0 2 0
80
+
81
+ 2021-06-03 0 0 1 1 1
82
+
83
+ 2021-06-04 0 2 0 0 1
84
+
85
+ 2021-05-12 1 1 1 0 2
86
+
87
+ 2021-05-13 0 0 1 0 0
88
+
89
+ 2021-05-14 1 0 0 1 2
90
+
91
+ 2021-05-15 3 1 1 3 0
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+
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+ 2021-05-16 0 2 0 0 0
94
+
95
+ 2021-05-17 0 1 0 2 0
96
+
97
+ 2021-05-18 1 0 2 2 3
98
+
99
+ 2021-05-19 0 1 0 0 0
100
+
101
+ 2021-05-20 2 2 0 0 2
102
+
103
+ 2021-05-21 0 0 0 0 0
104
+
105
+ 2021-05-22 0 2 2 2 0
106
+
107
+ 2021-05-23 0 0 1 2 1
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+
109
+ 2021-05-24 0 0 1 0 1
110
110
 
111
111
  ```
112
112
 
@@ -116,92 +116,110 @@
116
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117
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  >>> print(dates)
118
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119
+ >>> print(dates)
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+
119
121
  ['2021-04-29', '2021-04-30', '2021-05-01', '2021-05-02', '2021-05-03', '2021-05-04', '2021-05-05', '2021-05-06', '2021-05-07', '2021-05-08', '2021-05-11', '2021-05-12', '2021-05-13', '2021-05-14', '2021-05-15', '2021-05-16', '2021-05-17', '2021-05-18', '2021-05-19', '2021-05-20', '2021-05-21', '2021-05-22', '2021-05-23', '2021-05-24', '2021-05-25', '2021-05-26', '2021-05-27', '2021-05-28', '2021-05-29', '2021-05-30', '2021-05-31', '2021-06-01', '2021-06-02', '2021-06-03', '2021-06-04', '2021-05-12', '2021-05-13', '2021-05-14', '2021-05-15', '2021-05-16', '2021-05-17', '2021-05-18', '2021-05-19', '2021-05-20', '2021-05-21', '2021-05-22', '2021-05-23', '2021-05-24']
120
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121
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  >>> print(df)
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123
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  push1_start_date push2_start_date push3_start_date push4_start_date push5_start_date
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125
- 0 2021-05-13 <NA> <NA> 2021-05-20 <NA>
126
-
127
- 1 2021-05-25 <NA> 2021-05-18 <NA> 2021-05-27
128
-
129
- 2 2021-04-29 2021-05-27 2021-05-28 2021-05-18 2021-05-11
130
-
131
- 3 <NA> 2021-06-02 <NA> 2021-05-04 2021-05-15
132
-
133
- 4 2021-05-14 2021-05-12 <NA> 2021-05-16 2021-05-13
134
-
135
- 5 <NA> 2021-05-23 2021-05-19 2021-05-26 <NA>
136
-
137
- 6 2021-05-27 2021-05-01 <NA> <NA> 2021-05-15
138
-
139
- 7 <NA> 2021-05-17 2021-05-16 2021-05-17 2021-05-13
140
-
141
- 8 2021-05-21 2021-05-13 <NA> <NA> 2021-05-21
142
-
143
- 9 2021-06-03 <NA> <NA> 2021-05-16 2021-05-20
144
-
145
- 10 <NA> 2021-05-08 2021-05-02 2021-05-26 <NA>
146
-
147
- 11 <NA> 2021-05-15 <NA> 2021-06-04 2021-05-16
148
-
149
- 12 2021-05-07 2021-05-22 2021-05-04 2021-05-20 2021-05-02
150
-
151
- 13 <NA> <NA> 2021-05-01 <NA> 2021-05-17
152
-
153
- 14 2021-05-23 2021-05-14 <NA> 2021-05-21 <NA>
154
-
155
- 15 2021-05-02 2021-05-25 2021-05-23 2021-05-06 2021-05-21
156
-
157
- 16 2021-05-16 2021-05-12 2021-05-30 <NA> <NA>
158
-
159
- 17 2021-05-03 2021-05-01 <NA> 2021-05-19 2021-06-03
160
-
161
- 18 <NA> 2021-04-29 2021-05-22 2021-05-16 2021-05-12
162
-
163
- 19 2021-04-30 2021-05-24 2021-06-01 2021-05-17 2021-05-14
164
-
165
- 20 2021-05-14 2021-05-17 <NA> 2021-05-12 <NA>
166
-
167
- 21 2021-05-14 <NA> 2021-05-20 2021-05-27 <NA>
168
-
169
- 22 2021-05-06 2021-05-07 2021-05-22 2021-05-20 <NA>
170
-
171
- 23 2021-06-03 <NA> 2021-06-04 <NA> 2021-05-30
172
-
173
- 24 2021-05-14 <NA> 2021-05-03 2021-05-31 <NA>
174
-
175
- 25 2021-06-02 2021-05-31 2021-05-19 <NA> 2021-05-31
176
-
177
- 26 2021-05-30 2021-05-19 <NA> 2021-05-17 2021-05-15
178
-
179
- 27 2021-05-24 2021-05-23 2021-05-22 2021-05-17 2021-05-23
180
-
181
- 28 <NA> 2021-05-08 <NA> 2021-05-31 2021-05-12
182
-
183
- 29 2021-05-24 2021-05-12 2021-05-22 2021-05-04 <NA>
184
-
185
- 30 2021-05-18 2021-05-16 2021-05-08 <NA> 2021-05-28
186
-
187
- 31 2021-05-15 2021-05-14 <NA> 2021-05-30 <NA>
188
-
189
- 32 2021-05-17 2021-05-21 2021-05-22 <NA> 2021-05-13
190
-
191
- 33 2021-05-14 2021-05-11 2021-06-01 2021-05-20 2021-05-24
192
-
193
- 34 2021-05-23 <NA> 2021-05-24 2021-06-03 2021-05-04
194
-
195
- 35 <NA> <NA> 2021-05-06 2021-05-24 2021-05-23
196
-
197
- 36 <NA> <NA> <NA> 2021-05-25 <NA>
198
-
199
- 37 2021-05-03 2021-05-13 2021-05-06 2021-05-17 <NA>
200
-
201
- 38 2021-06-03 2021-04-29 2021-05-21 <NA> 2021-05-07
202
-
203
- 39 2021-05-25 2021-05-16 2021-05-15 2021-05-16 <NA>
127
+ 0 <NA> 2021-06-02 2021-05-06 <NA> 2021-05-20
128
+
129
+ 1 2021-05-26 <NA> <NA> 2021-05-14 <NA>
130
+
131
+ 2 <NA> 2021-05-16 <NA> 2021-05-15 2021-05-01
132
+
133
+ 3 <NA> <NA> 2021-06-03 2021-05-03 <NA>
134
+
135
+ 4 2021-05-18 2021-05-11 2021-05-12 2021-05-11 2021-05-23
136
+
137
+ 5 <NA> 2021-05-22 <NA> 2021-05-17 2021-05-18
138
+
139
+ 6 2021-05-06 <NA> 2021-05-15 <NA> <NA>
140
+
141
+ 7 <NA> <NA> <NA> <NA> 2021-05-11
142
+
143
+ 8 2021-05-30 2021-06-04 2021-05-18 2021-06-02 2021-05-18
144
+
145
+ 9 2021-05-01 2021-05-16 <NA> 2021-05-25 2021-05-14
146
+
147
+ 10 2021-05-12 <NA> <NA> <NA> 2021-05-24
148
+
149
+ 11 2021-05-06 2021-05-17 2021-05-24 2021-05-23 2021-05-18
150
+
151
+ 12 <NA> <NA> 2021-06-01 2021-05-18 2021-06-03
152
+
153
+ 13 <NA> 2021-05-11 <NA> 2021-06-02 2021-05-14
154
+
155
+ 14 2021-05-28 2021-06-01 2021-05-11 <NA> 2021-06-01
156
+
157
+ 15 <NA> 2021-05-11 <NA> 2021-05-17 <NA>
158
+
159
+ 16 2021-05-15 2021-05-15 <NA> <NA> 2021-06-04
160
+
161
+ 17 2021-05-14 2021-05-31 2021-05-30 <NA> <NA>
162
+
163
+ 18 2021-04-30 2021-05-08 <NA> 2021-05-03 2021-05-26
164
+
165
+ 19 2021-05-20 <NA> 2021-05-23 2021-05-15 <NA>
166
+
167
+ 20 <NA> 2021-05-29 2021-05-27 2021-05-15 2021-05-05
168
+
169
+ 21 <NA> 2021-05-22 <NA> <NA> 2021-05-12
170
+
171
+ 22 2021-05-20 2021-05-20 <NA> 2021-06-01 2021-05-25
172
+
173
+ 23 <NA> 2021-05-31 <NA> 2021-05-18 <NA>
174
+
175
+ 24 2021-05-05 2021-06-04 2021-05-22 2021-05-22 <NA>
176
+
177
+ 25 2021-05-03 2021-05-20 2021-05-18 <NA> <NA>
178
+
179
+ 26 2021-06-02 2021-05-12 <NA> 2021-05-22 2021-05-20
180
+
181
+ 27 2021-05-27 <NA> 2021-05-13 2021-06-03 <NA>
182
+
183
+ 28 2021-05-15 2021-05-19 <NA> <NA> <NA>
184
+
185
+ 29 2021-05-15 <NA> 2021-05-22 2021-05-23 2021-05-12
204
186
 
205
187
  ```
206
188
 
207
189
  処理
190
+
191
+ ```python
192
+
193
+ df_dates = pd.DataFrame({'dates': dates})
194
+
195
+
196
+
197
+ def count_one_column(df, column, df_dates):
198
+
199
+ df1 = df[[column]].copy()
200
+
201
+ df1['count'] = 1
202
+
203
+ df2 = df1.groupby(column).sum().reset_index()
204
+
205
+ df3 = pd.merge(df_dates, df2,
206
+
207
+ left_on='dates', right_on=column, how='left')
208
+
209
+ df4 = df3.drop(column, axis=1).set_index('dates')
210
+
211
+ df4.columns = [column]
212
+
213
+ df4.fillna(0.0, inplace=True)
214
+
215
+ df5 = df4[column].astype(int)
216
+
217
+ return df5
218
+
219
+
220
+
221
+ df_counts = pd.concat([count_one_column(df, column, df_dates) for column in df.columns], axis=1)
222
+
223
+ print(df_counts)
224
+
225
+ ```