How to use notin method in pandera

Best Python code snippet using pandera_python

filters.py

Source:filters.py Github

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1from rest_framework.filters import OrderingFilter2from django_filters.rest_framework import DjangoFilterBackend, FilterSet3from django_filters import rest_framework as filters4from distutils.util import strtobool5from .models import Platform, Institution, Parameter, Ferrybox, Cdf_Institution, getModel6from django import forms7#imports for custom lookups8from .lookups import NotEqual, NotIn9from django.db.models.fields import Field10BOOLEAN_CHOICES = (('false', 'False'), ('true', 'True'),)11class PlatformFilter(FilterSet):12 Field.register_lookup(NotEqual)13 #Field.register_lookup(NotIn)14 status = filters.TypedChoiceFilter(choices=BOOLEAN_CHOICES, coerce=strtobool)15 class Meta:16 model = Platform17 fields = {18 #filters:'exact','ne', 'lt', 'gt', 'lte', 'gte', 'in', icontains19 'id': ['exact', 'ne', 'in'], #notin20 'pid': ['exact', 'ne','in'], #notin21 'tspr': ['exact', 'ne'],22 'type': ['exact', 'ne', 'in'], #notin23 'inst': ['exact'], #einai kai kleidi gia institutions opote ftiaxnei drop down me ta institutions24 'inst__id': ['exact', 'in'],25 'dts': [ 'lt', 'gt', 'lte', 'gte', 'icontains'],26 'dte': [ 'lt', 'gt', 'lte', 'gte', 'icontains'],27 'lat': ['lt', 'gt', 'lte', 'gte'],28 'lon': ['lt', 'gt', 'lte', 'gte'],29 'status': [],30 'params' : ['icontains'], 31 'platform_code': [],32 'wmo': ['exact', 'ne', 'icontains'],33 'pi_name' : ['icontains'], 34 'author' : [],35 'contact' : [],36 'island': [],37 'pl_name' : [],38 'inst_ref' : [],39 'assembly_center' : ['exact', 'ne', 'in'],40 'site_code' : [],41 'source' : [],42 'cdf_inst': ['exact']43 }44class InstitutionFilter(FilterSet):45 Field.register_lookup(NotEqual)46 #Field.register_lookup(NotIn)47 class Meta:48 model = Institution49 fields = {50 #filters:'exact','ne', 'lt', 'gt', 'lte', 'gte', 'in', icontains51 'id': ['exact', 'ne', 'in'], #notin52 'name_native' : ['exact', 'ne', 'icontains'],53 'abrv' : ['exact', 'ne', 'in', 'icontains'], #notin54 'country' : ['exact', 'ne', 'in', 'icontains'], #notin55 'cdf_name' : [] 56 }57class Cdf_InstitutionFilter(FilterSet):58 Field.register_lookup(NotEqual)59 #Field.register_lookup(NotIn)60 class Meta:61 model = Cdf_Institution62 fields = {63 #filters:'exact','ne', 'lt', 'gt', 'lte', 'gte', 'in', icontains64 'id': ['exact', 'ne', 'in'], #notin65 'name' : ['exact', 'ne', 'icontains'],66 'inst_id' : ['exact', 'in']67 }68class ParameterFilter(FilterSet):69 Field.register_lookup(NotEqual)70 #Field.register_lookup(NotIn)71 class Meta:72 model = Parameter73 fields = {74 #filters:'exact','ne', 'lt', 'gt', 'lte', 'gte', 'in', icontains75 'id': ['exact', 'ne', 'in'], #notin76 'pname': ['exact', 'ne', 'in', 'icontains'], #notin77 'unit': ['exact', 'ne', 'in', 'icontains'], #notin78 'long_name': ['icontains'], 79 'stand_name': ['exact', 'ne', 'in', 'icontains'], #notin 80 'fval_qc': [], 81 'fval': [], 82 'category_long': ['exact', 'ne', 'in', 'icontains'], #notin83 'category_short': ['exact', 'ne', 'in', 'icontains'], #notin84 }85class FerryboxFilter(FilterSet):86 Field.register_lookup(NotEqual)87 #Field.register_lookup(NotIn)88 class Meta:89 model = Ferrybox90 fields = {91 #filters:'exact','ne', 'lt', 'gt', 'lte', 'gte', 'in', icontains92 'id': ['exact', 'ne', 'in'], #notin93 'dt': ['lt', 'gt', 'lte', 'gte', 'icontains'],94 'lat': ['lt', 'gt', 'lte', 'gte'],95 'lon': ['lt', 'gt', 'lte', 'gte'],96 'posqc': ['exact', 'ne', 'in','lt', 'gt', 'lte', 'gte'], #notin97 'pres': ['lt', 'gt', 'lte', 'gte'],98 'presqc': ['exact', 'ne', 'in', 'lt', 'gt', 'lte', 'gte'], #notin99 'param': ['exact'],100 'param__id' : ['exact','ne', 'in'], #notin101 'val': ['lt', 'gt', 'lte', 'gte'],102 'valqc': ['exact', 'ne', 'in', 'lt', 'gt', 'lte', 'gte'], #notin103 'route_id': ['exact'],...

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filter_dict.py

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1filters = {2 'assets': {3 'id': {'operators': ['equals', 'like', 'in', 'notIn']},4 'name': {'operators': ['equals', 'like', 'in', 'notIn']},5 'first_seen': {'name': 'firstSeen', 'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},6 'last_seen': {'name': 'lastSeen', 'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},7 'addresses': {'operators': ['contains', 'like', 'notIn']},8 'direct_addresses': {'name': 'directAddresses', 'operators': ['contains', 'like', 'notIn']},9 'type': {'operators': ['equals', 'like', 'in', 'notIn']},10 'purdue_level': {'name': 'purdueLevel', 'operators': ['equals', 'like', 'in', 'notIn']},11 'vendor': {'operators': ['equals', 'like', 'in', 'notIn']},12 'run_status': {'name': 'runStatus', 'operators': ['equals', 'like', 'in', 'notIn']},13 'runStatusTime': {'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},14 'location': {'operators': ['equals', 'like', 'in', 'notIn']},15 'description': {'operators': ['equals', 'like', 'in', 'notIn']},16 'os': {'operators': ['equals', 'like', 'in', 'notIn']},17 'family': {'operators': ['equals', 'like', 'in', 'notIn']},18 'modelName': {'operators': ['equals', 'like', 'in', 'notIn']},19 'firmware': {'operators': ['equals', 'like', 'in', 'notIn']},20 'slot': {'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},21 'backplane': {'operators': ['equals', 'like', 'in', 'notIn']},22 'risk': {'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},23 'criticality': {'operators': ['equals', 'like', 'in', 'less', 'greater', 'notIn']},24 'site': {'operators': ['equals', 'like', 'in', 'notIn']},25 'hidden': {'operators': ['equals', 'like', 'in', 'notIn']},26 'customField1': {'operators': ['equals', 'like', 'in', 'notIn']},27 'customField2': {'operators': ['equals', 'like', 'in', 'notIn']},28 'customField3': {'operators': ['equals', 'like', 'in', 'notIn']},29 'customField4': {'operators': ['equals', 'like', 'in', 'notIn']},30 'customField5': {'operators': ['equals', 'like', 'in', 'notIn']},31 'customField6': {'operators': ['equals', 'like', 'in', 'notIn']},32 'customField7': {'operators': ['equals', 'like', 'in', 'notIn']},33 'customField8': {'operators': ['equals', 'like', 'in', 'notIn']},34 'customField9': {'operators': ['equals', 'like', 'in', 'notIn']},35 'customField10': {'operators': ['equals', 'like', 'in', 'notIn']},36 }...

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temp.py

Source:temp.py Github

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1# -*- coding: utf-8 -*-2"""34"""56'''71. 先把两个表(old1,old2)合并, 82. 然后取出重复的数据, 保留一条93. 保存到新表new1104. 吧old1表和new1表合并115. 然后取出重复的数据并删除,得到差集,就是在old2中但不在old1中的数据126. 吧old2表和new1表合并137. 然后取出重复的数据并删除,得到差集,就是在old1中但不在old2中的数据14'''151617import pandas as pd181920# openexcel21data1 = pd.read_excel('C:\\Users\\JZ\\.spyder-py3\\1.xlsx')22df1 = data1['Server Name'] # 读取列名为Server Name的内容23#print(df1)2425data2 = pd.read_excel('C:\\Users\\JZ\\.spyder-py3\\2.xlsx')26df2 = data2['Host'] # 读取列名为Host的内容27#print(df2)282930# 1.merge_excel31res = pd.concat([df1, df2], axis=0, ignore_index=True)32#print(res)333435# 2,3.get_compilation36#compilation_del = res.drop_duplicates(keep=False)37compilation = res.drop_duplicates()38compilation.to_excel('C:\\Users\\JZ\\.spyder-py3\\res.xlsx')39#print(compilation_del)40#print(compilation)4142# 4.merge ITAM and compilation43notin_df1_file = pd.concat([df1, compilation], axis=0, ignore_index=True)44#print(notin_df1_file)4546# 5.get subtraction47inventory_notin_itam = notin_df1_file.drop_duplicates(keep=False)48#print(inventory_notin_itam)49inventory_notin_itam.to_excel('C:\\Users\\JZ\\.spyder-py3\\inventory_notin_itam.xlsx')5051# 6.merge inventory and compilation52notin_df2_file = pd.concat([df2, compilation],axis=0, ignore_index=True)53#print(notin_df2_file)5455# 7.get subtraction56itam_notin_inventory = notin_df2_file.drop_duplicates(keep=False)57#print(itam_notin_inventory)58itam_notin_inventory.to_excel('C:\\Users\\JZ\\.spyder-py3\\itam_notin_inventory.xlsx')596061626364 ...

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