用Python处理csv文件的一些小玩意儿

摘要：整理了一些个人在利用处理文件时经常用到的一些自定义方法，放在这里主要方便自己查阅，也可以给其他人做参考目录输出文件某列的匹配不匹配的记录调整文件的列的顺序转换器抽取特定列除去完全重复的记录根据列名排序键值互换输出文件某列的匹配不匹配的记录主

整理了一些个人在利用python处理csv文件时经常用到的一些自定义方法，放在这里主要方便自己查阅，也可以给其他人做参考

输出CSV文件某列的匹配/不匹配的记录

调整csv文件的列的顺序

CSV转换器

抽取特定列

除去完全重复的记录

根据列名排序

键值互换

主要用于从csv文件中抽取出匹配特定列的特定字段集合的记录，比如现有这么一个csv文件（表格化后）

需要输出其中age为23的记录到新的csv文件，则我们可以先把23这么个关键词用一个列表收集起来，然后通过下列代码从csv文件中找出所有符合条件的记录并输出

import sys
import csv

# try to fix "_csv.Error: field larger than field limit (131072)"
csv.field_size_limit(sys.maxint)

# write to common csv file with delimiter ","
# output the rows with matched id in id_list to a new csv file
def csv_match(id_list,key,input_file,output_file):
    with open(input_file, "rb") as f:
        reader = csv.DictReader(f)
        rows = [row for row in reader if row[key] in set(id_list)]

    header = rows[0].keys()
    with open(output_file, "w") as f:
        f.write(",".join(header))
        f.write("
")
        for data in rows:
            f.write(",".join(data[h] for h in header))
            f.write("
")

调用的时候：

lst=["23"]
csv_match(lst,"age","in.csv","out.csv")

key为需要匹配的列名，另外我们也可以提取不符合该条件的记录，‘取个反’就行了

# output the rows with not matched id in id_list to a new csv file
def csv_not_match(id_list, key, input_file, output_file):
    with open(input_file, "rb") as f:
        reader = csv.DictReader(f)
        rows = [row for row in reader if not row[key] in set(id_list)]

    header = rows[0].keys()
    with open(output_file, "w") as f:
        f.write(",".join(header))
        f.write("
")
        for data in rows:
            f.write(",".join(data[h] for h in header))
            f.write("
")

对于需要判断csv文件中多个列的值的情况，只需修改对应的判别条件和传入参数情况即可

# output the rows with matched key1 or key2 in refer_list to a new csv file
# @params
# refer_list: the list referred to
# key,key2: column name of csv file to check the value in the refer_list or not
def csv_match2(refer_list, key1, key2, input_file, output_file):
    with open(input_file, "rb") as f:
        reader = csv.DictReader(f)
        rows = [row for row in reader if (row[key1] in set(refer_list)) or (row[key2] in set(refer_list))]

    header = rows[0].keys()
    with open(output_file, "w") as f:
        f.write(",".join(header))
        f.write("
")
        for data in rows:
            f.write(",".join(data[h] for h in header))
            f.write("
")

有时候我们输出的或者拿到的csv文件的列的顺序不够‘人性化’，为了让我们看起来更加直观，更舒服一点，我们可以按照我们的需要调整列的顺序

import csv
# reorder the column of the csv file to what you want
def csv_reorder(in_file, out_file,lst_order):
    with open(in_file, "rb") as infile, open(out_file, "wb") as outfile:
        fieldnames=lst_order
        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
        writer.writeheader()
        for row in csv.DictReader(infile):
            writer.writerow(row)

其中lst_order为我们需要的列名顺序，用list存储，举个例子

season_id,league_name,league_size
2003,scottish-premiership,12
2016,1-hnl,10
2004,alka-superligaen,12
2006,allsvenskan,14
1992,premier-league,22
...

现在我们想调整他的顺序，按照league_name,season_id,league_size的顺序重新组合一下
则调用

lst_order = ["league_name","season_id","league_size"]
csv_reorder("leagues_size.csv", "leagues_size_new.csv", lst_order)

得到结果

league_name,season_id,league_size
scottish-premiership,2003,12
1-hnl,2016,10
alka-superligaen,2004,12
allsvenskan,2006,14
premier-league,1992,22
...

这个主要是用来进行csv和python的一些内置的容器例如list,dict之类的转换，包括一些特殊的多级字典，或者是嵌套列表的字典等等，这里只是把他们打个包放在一起，具体的可以参照我之前写的一篇文章

import csv

#---------------------------------------------------csv <--> dict--------------------------------------------

# convert csv file to dict
# @params:
# key/value: the column of original csv file to set as the key and value of dict
def csv2dict(in_file,key,value):
    new_dict = {}
    with open(in_file, "rb") as f:
        reader = csv.reader(f, delimiter=",")
        fieldnames = next(reader)
        reader = csv.DictReader(f, fieldnames=fieldnames, delimiter=",")
        for row in reader:
            new_dict[row[key]] = row[value]
    return new_dict


# convert csv file to dict(key-value pairs each row)
# default: set row[0] as key and row[1] as value of the dict
def row_csv2dict(csv_file):
    dict_club={}
    with open(csv_file)as f:
        reader=csv.reader(f,delimiter=",")
        for row in reader:
            dict_club[row[0]]=row[1]
    return dict_club

# write dict to csv file
# write each key/value pair on a separate row
def dict2csv(dict, file):
    with open(file, "wb") as f:
        w = csv.writer(f)
        # write each key/value pair on a separate row
        w.writerows(dict.items())

# write dict to csv file
# write all keys on one row and all values on the next
def dict2csv2(dict, file):
    with open(file, "wb") as f:
        w = csv.writer(f)
        # write all keys on one row and all values on the next
        w.writerow(dict.keys())
        w.writerow(dict.values())

# build a dict of list like {key:[...element of lst_inner_value...]}
# key is certain column name of csv file
# the lst_inner_value is a list of specific column name of csv file
def build_list_dict(source_file, key, lst_inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            for element in lst_inner_value:
                new_dict.setdefault(row[key], []).append(row[element])
    return new_dict
# sample:
# test_club=build_list_dict("test_info.csv","season",["move from","move to"])
# print test_club


# build specific nested dict from csv files
# @params:
#   source_file
#   outer_key:the outer level key of nested dict
#   inner_key:the inner level key of nested dict,and rest key-value will be store as the value of inner key
def build_level2_dict(source_file,outer_key,inner_key):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        reader = csv.reader(csv_file, delimiter=",")
        fieldnames = next(reader)
        inner_keyset=fieldnames
        inner_keyset.remove(outer_key)
        inner_keyset.remove(inner_key)
        csv_file.seek(0)
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            item = new_dict.get(row[outer_key], dict())
            item[row[inner_key]] = {k: row[k] for k in inner_keyset}
            new_dict[row[outer_key]] = item
    return new_dict

# build specific nested dict from csv files
# @params:
#   source_file
#   outer_key:the outer level key of nested dict
#   inner_key:the inner level key of nested dict
#   inner_value:set the inner value for the inner key
def build_level2_dict2(source_file,outer_key,inner_key,inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            item = new_dict.get(row[outer_key], dict())
            item[row[inner_key]] = row[inner_value]
            new_dict[row[outer_key]] = item
    return new_dict

# build specific nested dict from csv files
# @params:
#   source_file
#   outer_key:the outer level key of nested dict
#   lst_inner_value: a list of column name,for circumstance that the inner value of the same outer_key are not distinct
#   {outer_key:[{pairs of lst_inner_value}]}
def build_level2_dict3(source_file,outer_key,lst_inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            new_dict.setdefault(row[outer_key], []).append({k: row[k] for k in lst_inner_value})
    return new_dict

# build specific nested dict from csv files
# @params:
#   source_file
#   outer_key:the outer level key of nested dict
#   lst_inner_value: a list of column name,for circumstance that the inner value of the same outer_key are not distinct
#   {outer_key:{key of lst_inner_value:[...value of lst_inner_value...]}}
def build_level2_dict4(source_file,outer_key,lst_inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            # print row
            item = new_dict.get(row[outer_key], dict())
            # item.setdefault("move from",[]).append(row["move from"])
            # item.setdefault("move to", []).append(row["move to"])
            for element in lst_inner_value:
                item.setdefault(element, []).append(row[element])
            new_dict[row[outer_key]] = item
    return new_dict

# build specific nested dict from csv files
# @params:
#   source_file
#   outer_key:the outer level key of nested dict
#   lst_inner_key:a list of column name
#   lst_inner_value: a list of column name,for circumstance that the inner value of the same lst_inner_key are not distinct
#   {outer_key:{lst_inner_key:[...lst_inner_value...]}}
def build_list_dict2(source_file,outer_key,lst_inner_key,lst_inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            # print row
            item = new_dict.get(row[outer_key], dict())
            item.setdefault(row[lst_inner_key], []).append(row[lst_inner_value])
            new_dict[row[outer_key]] = item
    return new_dict

# dct=build_list_dict2("test_info.csv","season","move from","move to")

# build specific nested dict from csv files
# a dict like {outer_key:{inner_key1:{inner_key2:{rest_key:rest_value...}}}}
# the params are extract from the csv column name as you like
def build_level3_dict(source_file,outer_key,inner_key1,inner_key2):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        reader = csv.reader(csv_file, delimiter=",")
        fieldnames = next(reader)
        inner_keyset=fieldnames
        inner_keyset.remove(outer_key)
        inner_keyset.remove(inner_key1)
        inner_keyset.remove(inner_key2)
        csv_file.seek(0)
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            item = new_dict.get(row[outer_key], dict())
            sub_item = item.get(row[inner_key1], dict())
            sub_item[row[inner_key2]] = {k: row[k] for k in inner_keyset}
            item[row[inner_key1]] = sub_item
            new_dict[row[outer_key]] = item
    return new_dict

# build specific nested dict from csv files
# a dict like {outer_key:{inner_key1:{inner_key2:inner_value}}}
# the params are extract from the csv column name as you like
def build_level3_dict2(source_file,outer_key,inner_key1,inner_key2,inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            item = new_dict.get(row[outer_key], dict())
            sub_item = item.get(row[inner_key1], dict())
            sub_item[row[inner_key2]] = row[inner_value]
            item[row[inner_key1]] = sub_item
            new_dict[row[outer_key]] = item
    return new_dict
   

# build specific nested dict from csv files
# a dict like {outer_key:{inner_key1:{inner_key2:[inner_value]}}}
# for multiple inner_value with the same inner_key2,thus gather them in a list
# the params are extract from the csv column name as you like
def build_level3_dict3(source_file,outer_key,inner_key1,inner_key2,inner_value):
    new_dict = {}
    with open(source_file, "rb")as csv_file:
        data = csv.DictReader(csv_file, delimiter=",")
        for row in data:
            item = new_dict.get(row[outer_key], dict())
            sub_item = item.get(row[inner_key1], dict())
            sub_item.setdefault(row[inner_key2], []).append(row[inner_value])
            item[row[inner_key1]] = sub_item
            new_dict[row[outer_key]] = item
    return new_dict

#----------------------------------------------------------------------------------------------------------

#---------------------------------------------------csv <--> list--------------------------------------------

def list2csv(list, file):
# def list2csv(list):
#     wr = csv.writer(open(file, "wb"), quoting=csv.QUOTE_ALL)
    wr=open(file,"w")
    for word in list:
        # print "".join(word)
        # wr.writerow([word])
        wr.write(word+"
")
        # wr.writerow(str.split(word,""")[0])
        # print [word]

# test_list = ["United States", "China", "America", "England"]

# list2csv(test_list,"small_test.csv")

# write nested list of dict to csv
def nestedlist2csv(list, out_file):
    with open(out_file, "wb") as f:
        w = csv.writer(f)
        fieldnames=list[0].keys()  # solve the problem to automatically write the header
        w.writerow(fieldnames)
        for row in list:
            w.writerow(row.values())


# my_list = [{"players.vis_name": "Khazri", "players.role": "Midfielder", "players.country": "Tunisia",
#             "players.last_name": "Khazri", "players.player_id": "989", "players.first_name": "Wahbi",
#             "players.date_of_birth": "08/02/1991", "players.team": "Bordeaux"},
#            {"players.vis_name": "Khazri", "players.role": "Midfielder", "players.country": "Tunisia",
#             "players.last_name": "Khazri", "players.player_id": "989", "players.first_name": "Wahbi",
#             "players.date_of_birth": "08/02/1991", "players.team": "Sunderland"},
#            {"players.vis_name": "Lewis Baker", "players.role": "Midfielder", "players.country": "England",
#             "players.last_name": "Baker", "players.player_id": "9574", "players.first_name": "Lewis",
#             "players.date_of_birth": "25/04/1995", "players.team": "Vitesse"}
#            ]

# nestedlist2csv(my_list, "dict2csv_test.csv")



# collect and convert the first column of csv file to list
def csv2list(csv_file):
    lst = []
    with open(csv_file, "rb")as f:
        reader = csv.reader(f, delimiter=",")
        for row in reader:
            lst.append(row[0])
    return list(set(lst))
#----------------------------------------------------------------------------------------------------------

抽取特定列的所有值并存储于列表

根据下标抽取特定列到某个新的csv文件

获取某列原始的数据并保存为列表

# get certain column value of csv(for common csv file(","))
def get_origin_column_value(file, column_name):
    with open(file, "rb") as f:
        role_list = []
        reader = csv.reader(f, delimiter=",")
        fieldnames = next(reader)
        reader = csv.DictReader(f, fieldnames=fieldnames, delimiter=",")
        for row in reader:
            role_list.append(row[column_name])
        return role_list

对于某些有特殊需要的可以直接修改代码，比如对原始的列的值进行除重和排序后获取，如下

# get certain column value of csv(for common csv file(",")),and judge if it"s repeated
def get_column_value2(file, column_name):
    with open(file, "rb") as f:
        role_list = []
        reader = csv.reader(f, delimiter=",")
        fieldnames = next(reader)
        reader = csv.DictReader(f, fieldnames=fieldnames, delimiter=",")
        for row in reader:
            role_list.append(row[column_name])
        role_set = set(role_list)
        return sorted(list(role_set))

import csv
# extract certain column from csv file according to the column#
def column_extract(file_in,file_out,index):
    with open(file_in,"r") as f_in:
        with open(file_out,"w") as f_out:
            for line in f_in:
                f_out.write(line.split(",")[index])
                f_out.write("
") # comment if a new line already exists

# eliminated the completely repeated record in repeated file for further analysis
def eliminate_repeated_row(in_file,out_file):
    with open(in_file,"rb") as in_file,open(out_file,"wb")as out_file:
        seen=set()
        for line in in_file:
            # print line
            if line in seen:continue

            seen.add(line)
            out_file.write(line)

# sort the csv file by certain column to put the similar record together for further analysis
def sort_csv_byColumn(in_file, out_file,column_name):
    with open(in_file, "rb") as f:
        reader = csv.reader(f, delimiter=",")
        fieldnames = next(reader)
        reader = csv.DictReader(f, fieldnames=fieldnames, delimiter=",")
        sorted_list = sorted(reader, key=lambda row: row[column_name], reverse=True)
        # print sorted_list
        csv_converter.nestedlist2csv(sorted_list, out_file)

例如我们按照league_name排序(注意这里调用了csv转换器中的方法将列表的字典转换为csv文件)

sort_csv_byColumn("leagues_size.csv","ordered_leagues_size.csv","league_name")

得到结果

season_id,league_name,league_size
2016,ykkonen,9
2003,ykkonen,14
2005,ykkonen,14
2006,ykkonen,14
2007,ykkonen,14
2010,ykkonen,13
2011,ykkonen,10
2009,ykkonen,14
2008,ykkonen,14
2012,ykkonen,10
2013,ykkonen,10
2014,ykkonen,10
2015,ykkonen,10
2016,wiener-stadtliga,16
1988,wiener-stadtliga,16
1993,wiener-stadtliga,16
1994,wiener-stadtliga,16
1995,wiener-stadtliga,16
1996,wiener-stadtliga,16
1997,wiener-stadtliga,16
1998,wiener-stadtliga,16

如果我们按league_size排序

sort_csv_byColumn("leagues_size.csv",
                    "orderedbysize_leagues_size.csv","league_size")

得到结果

season_id,league_name,league_size
2008,virsliga,9
2010,virsliga,9
2012,a-lyga,9
2012,a-pojat-sm-sarja,9
2013,a-pojat-sm-sarja,9
1953,salzburger-liga,9
2010,3-lig-grup-1,9
2013,armenian-first-league,9
2016,ykkonen,9
2014,stirling-sports-premiership,9
2014,hong-kong-premier-league,9
2015,hong-kong-premier-league,9
1996,s-league,9
2015,s-league,9
2013,united-football-league,9
2016,i-league,9

csv文件每一条记录其实可以看作是一个字典，有时csv文件里有不同的键对应同一个值的情况，我们想讲记录反转一下，即让值作为键，对应的键作为值

# return a dict with the same value in original as new key and keys as value
def dict_same_value(original_dict):
    new_dict={}
    for k,v in original_dict.iteritems():
        new_dict.setdefault(v,[]).append(k)
    return new_dict

最后欢迎大家fork关于这个的github上的repository，一起丰富更多好玩的功能~

更新日志
1、2016-12-18 修复了从csv文件中获取特定的列的值保存为集合的问题，而是存储为原始的列表
2、2016-12-22 改进了csv转换器中的构建二级字典的方法，使其变得更加灵活
3、2016年12月24日14:57:48 在csv转换器部分加入三级字典构造的参照方法
4、2017年1月9日11:28:45 在csv转换器部分，三级字典构造中，加入了最内部存储值为列表的构造方法
5、2017年1月16日10:43:41 在csv转换器部分，加入了构造列表字典的方法以及构造特殊的二级字典（内部为列表）的方法
6、2017年2月9日10:58:17 在csv转换器部分，加入了新的构造特殊的二级字典（内部为列表）的方法
7、2017年2月10日11:21:45 在csv转换器部分，改进了简单的csv文件转换为字典的方法，此外在Csv_Match部分，加入了匹配判断多个列对应的元素条件的方法