摘要：整理了一些個人在利用處理文件時經常用到的一些自定義方法，放在這里主要方便自己查閱，也可以給其他人做參考目錄輸出文件某列的匹配不匹配的記錄調整文件的列的順序轉換器抽取特定列除去完全重復的記錄根據列名排序鍵值互換輸出文件某列的匹配不匹配的記錄主

整理了一些個人在利用python處理csv文件時經常用到的一些自定義方法，放在這里主要方便自己查閱，也可以給其他人做參考

輸出CSV文件某列的匹配/不匹配的記錄

調整csv文件的列的順序

CSV轉換器

抽取特定列

除去完全重復的記錄

根據列名排序

鍵值互換

主要用于從csv文件中抽取出匹配特定列的特定字段集合的記錄，比如現有這么一個csv文件（表格化后）

需要輸出其中age為23的記錄到新的csv文件，則我們可以先把23這么個關鍵詞用一個列表收集起來，然后通過下列代碼從csv文件中找出所有符合條件的記錄并輸出

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("
")

調用的時候：

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

key為需要匹配的列名，另外我們也可以提取不符合該條件的記錄，‘取個反’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("
")

對于需要判斷csv文件中多個列的值的情況，只需修改對應的判別條件和傳入參數情況即可

# 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("
")

有時候我們輸出的或者拿到的csv文件的列的順序不夠‘人性化’，為了讓我們看起來更加直觀，更舒服一點，我們可以按照我們的需要調整列的順序

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為我們需要的列名順序，用list存儲，舉個例子

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
...

現在我們想調整他的順序，按照league_name,season_id,league_size的順序重新組合一下
則調用

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

得到結果

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
...

這個主要是用來進行csv和python的一些內置的容器例如list,dict之類的轉換，包括一些特殊的多級字典，或者是嵌套列表的字典等等，這里只是把他們打個包放在一起，具體的可以參照我之前寫的一篇文章

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儲于列表

根據下標抽取特定列到某個新的csv文件

獲取某列原始的數據并保存為列表

# 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

對于某些有特殊需要的可以直接修改代碼，比如對原始的列的值進行除重和排序后獲取，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)

例如我們按照league_name排序(注意這里調用了csv轉換器中的方法將列表的字典轉換為csv文件)

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

得到結果

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

如果我們按league_size排序

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

得到結果

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文件每一條記錄其實可以看作是一個字典，有時csv文件里有不同的鍵對應同一個值的情況，我們想講記錄反轉一下，即讓值作為鍵，對應的鍵作為值

# 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

最后歡迎大家fork關于這個的github上的repository，一起豐富更多好玩的功能~

更新日志
1、2016-12-18 修復了從csv文件中獲取特定的列的值保存為集合的問題，而是存儲為原始的列表
2、2016-12-22 改進了csv轉換器中的構建二級字典的方法，使其變得更加靈活
3、2016年12月24日14:57:48 在csv轉換器部分加入三級字典構造的參照方法
4、2017年1月9日11:28:45 在csv轉換器部分，三級字典構造中，加入了最內部存儲值為列表的構造方法
5、2017年1月16日10:43:41 在csv轉換器部分，加入了構造列表字典的方法以及構造特殊的二級字典（內部為列表）的方法
6、2017年2月9日10:58:17 在csv轉換器部分，加入了新的構造特殊的二級字典（內部為列表）的方法
7、2017年2月10日11:21:45 在csv轉換器部分，改進了簡單的csv文件轉換為字典的方法，此外在Csv_Match部分，加入了匹配判斷多個列對應的元素條件的方法