Pandas筛选某列过滤的方法
通过dataframe的第二个条件,进行筛选
#make字段异常值清洗 new = data[['make', 'model', 'instance_id']] new['make_model'] = new['make']+':::'+new['model'] new.head(3)
# new.make_model.value_counts() # 统计make_model列属性值出现的次数 new.make_model.value_counts()[new.make_model.value_counts() <= 200] """ OPPO:::OPPO+A59st 200 OPPO:::3007 200 Xiaomi:::Redmi%20Note%203 200 Meizu:::MEIZU-M6 199 samsung:::SM-N9006 199 ... OPPO,OPPO A53,A53:::OPPO A53 1 boway Ujs15:::boway U15 1 BaiMao:::BM I8 1 vivo:::vivoy75a 1 SUPERJO:::SUPERJO 1 Name: make_model, Length: 15597, dtype: int64 """
找出符合第二列筛选条件的index(这里index不是0-n,而是刚才value_counts()的index)
(new.make_model.value_counts()[new.make_model.value_counts() &编程客栈lt;= 200]).index """ Index(['OPPO:::OPPO+A59sphpt', 'OPPO:::3007', 'Xiaomi:::Redmi%20Note%203', 'Meizu:::MEIZU-M6', 'samsung:::SM-N9006', 'Coolpad:::MTS-T0', 'OPPO R11st:::OPPO R11st', 'Blephone:::lephone T7A', 'GIONEE:::GN9011', 'Meizu:::PRO 7-S', ... 'HUAWEI:::HUAWEI%25252BG7-UL20', 'VOLTE:::L3', 'GIONEE:::GN868', 'alps:::SOP-i9', 'GT-I9300I:::GT-I9300I', 'OPPO,OPPO A53,A53:::OPPO A53', 'boway U15:::boway U15', 'BaiMao:::BM I8', 'vivo:::vivoy75a', 'SUPERJO:::SUPERJO'], dtype='object', length=15597) """
new.make_model """ 0 HUAWEI:::HUAWEI-CAZ-AL10 1 Xiaomi:::Redmi Note 4 2 OPPO:::OPPO+R11s 3 NaN 4 Apple:::iPhone 7 ... 1041669 OPPO:::OPPO-R9s 1041670 Xiaomi:::MI-5X 1041671 vivo:::vivo Y37 1041672 vivo:::vivo%20Y75A 1041673 OPPO:::A31 Name: make_model, Length: 1041674, dtype: object """
dataframe.loc(行索引, 列名)
# 在make_model列, # 定位符合 new.make_model.isin((new.make_model.value_counts()[new.make_model.value_counts() <= 200]).index) 的行 # new.loc[new.make_model.isin((new.make_model.value_counts()[new.make_model.value_counts() <= 200]).index), 'make_model'] = 'other' #去除低频词
再感受下第二个case
data['day'] = data['time'].apply(lambda x : int(time.strftime("%d", time.localtime(x)))) data['period'] = data['day'] data[['period']].head(3)
data['period'].unique() # array([29, 30, 31, 27, 1, 2, 28, 3])
直接用列筛选
[dawww.devze.comta['period']<27] """ [0 False 1 False 2 False 3 False 4 False ... 1041669 True 1041670 True 1041671 True 1041672 True 1041673 True Name: period, Length: 1041674, dtype: bool] """
data['period']<27 """ 0开发者_开发培训 False 1 False 2 False 3 False 4 False ... 1041669 True 1041670 True 1041671 True 1041672 True 1041673 True Name: period, Length: 1041674, dtype: bool """
挑选period列,值<27的行(已成功挑选)
data['period'][data['period']<27] """ 950 1 951 1 952 1 953 1 954 1 .. 1041669 3 1041670 3 1041671 3 1041672 3 1041673 3 Name: period, Length: 348536, dtype: int64 """ data['period'][data['period']<27] = data['period'][data['period']<27] + 31
这样可以使用head展示
data[['period']][data['period']<27].head(3)
还有种单列就能筛选的方法
t2['receive_number'] = t2.date_received.apply(lambda s:len(s.split(':'))) t2 = t2[t2.receive_number>1] t2.head(3)
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