时间:2021-06-09 python教程 查看: 1012
1.将一个大Excel等份拆成多个Excel
2.将多个小Excel合并成一个大Excel并标记来源
work_dir="./course_datas/c15_excel_split_merge"
splits_dir=f"{work_dir}/splits"
import os
if not os.path.exists(splits_dir):
os.mkdir(splits_dir)
import pandas as pd
No output
df_source = pd.read_excel(f"{work_dir}/crazyant_blog_articles_source.xlsx")
No output
df_source.head()
idtitletags
02585Tensorflow怎样接收变长列表特征python,tensorflow,特征工程
12583Pandas实现数据的合并concatpandas,python,数据分析
22574Pandas的Index索引有什么用途?pandas,python,数据分析
32564机器学习常用数据集大全python,机器学习
42561一个数据科学家的修炼路径数据分析
df_source.index
RangeIndex(start=0, stop=258, step=1)
df_source.shape
(258, 3)
total_row_count = df_source.shape[0]
total_row_count
258
1.使用df.iloc方法,将一个大的dataframe,拆分成多个小dataframe
2.将使用dataframe.to_excel保存每个小Excel
1、计算拆分后的每个excel的行数
# 这个大excel,会拆分给这几个人
user_names = ["xiao_shuai", "xiao_wang", "xiao_ming", "xiao_lei", "xiao_bo", "xiao_hong"]
No output
# 每个人的任务数目
split_size = total_row_count // len(user_names)
if total_row_count % len(user_names) != 0:
split_size += 1
split_size
43
2、拆分成多个dataframe
df_subs = []
for idx, user_name in enumerate(user_names):
# iloc的开始索引
begin = idx*split_size
# iloc的结束索引
end = begin+split_size
# 实现df按照iloc拆分
df_sub = df_source.iloc[begin:end]
# 将每个子df存入列表
df_subs.append((idx, user_name, df_sub))
No output
3、将每个datafame存入excel
for idx, user_name, df_sub in df_subs:
file_name = f"{splits_dir}/crazyant_blog_articles_{idx}_{user_name}.xlsx"
df_sub.to_excel(file_name, index=False)
No output
1.遍历文件夹,得到要合并的Excel文件列表
2.分别读取到dataframe,给每个df添加一列用于标记来源
3.使用pd.concat进行df批量合并
4.将合并后的dataframe输出到excel
1. 遍历文件夹,得到要合并的Excel名称列表
import os
excel_names = []
for excel_name in os.listdir(splits_dir):
excel_names.append(excel_name)
excel_names
['crazyant_blog_articles_0_xiao_shuai.xlsx',
'crazyant_blog_articles_1_xiao_wang.xlsx',
'crazyant_blog_articles_2_xiao_ming.xlsx',
'crazyant_blog_articles_3_xiao_lei.xlsx',
'crazyant_blog_articles_4_xiao_bo.xlsx',
'crazyant_blog_articles_5_xiao_hong.xlsx']
2. 分别读取到dataframe
df_list = []
for excel_name in excel_names:
# 读取每个excel到df
excel_path = f"{splits_dir}/{excel_name}"
df_split = pd.read_excel(excel_path)
# 得到username
username = excel_name.replace("crazyant_blog_articles_", "").replace(".xlsx", "")[2:]
print(excel_name, username)
# 给每个df添加1列,即用户名字
df_split["username"] = username
df_list.append(df_split)
crazyant_blog_articles_0_xiao_shuai.xlsx xiao_shuai
crazyant_blog_articles_1_xiao_wang.xlsx xiao_wang
crazyant_blog_articles_2_xiao_ming.xlsx xiao_ming
crazyant_blog_articles_3_xiao_lei.xlsx xiao_lei
crazyant_blog_articles_4_xiao_bo.xlsx xiao_bo
crazyant_blog_articles_5_xiao_hong.xlsx xiao_hong
3. 使用pd.concat进行合并
df_merged = pd.concat(df_list)
No output
df_merged.shape
(258, 4)
df_merged.head()
id title tags username
0 2585 Tensorflow怎样接收变长列表特征 python,tensorflow,特征工程 xiao_shuai
1 2583 Pandas实现数据的合并concat pandas,python,数据分析 xiao_shuai
2 2574 Pandas的Index索引有什么用途? pandas,python,数据分析 xiao_shuai
3 2564 机器学习常用数据集大全 python,机器学习 xiao_shuai
4 2561 一个数据科学家的修炼路径 数据分析 xiao_shuai
df_merged["username"].value_counts()
xiao_hong 43
xiao_bo 43
xiao_shuai 43
xiao_lei 43
xiao_wang 43
xiao_ming 43
Name: username, dtype: int64
xiao_hong 43xiao_bo 43xiao_shuai 43xiao_lei 43xiao_wang 43xiao_ming 43Name: username, dtype: int64
<p><strong>4. 将合并后的dataframe输出到excel</strong></p> ```python df_merged.to_excel(f"{work_dir}/crazyant_blog_articles_merged.xlsx", index=False)
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