init

.gitignore

@@ -0,0 +1,124 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+
+/yi*
+/ajaja
+/lllll
+
+/.idea
+*.zip
+/exportToHTML

A001_课程简介/A001.py

@@ -0,0 +1,199 @@
+"""
+输出
+/Users/Yi/我的python教程/pandas办公自动化_备课/data_out/2019全平台销售总表.xlsx
+"""
+import pandas as pd
+import numpy as np
+import os
+import sys
+from time import time
+
+from openpyxl import load_workbook
+from openpyxl.drawing.image import Image
+
+pd.options.display.max_columns = 888
+pd.options.display.max_rows = 888
+
+out_xlsx_title_1 = ['货号', '商品名称', '图片', '尺码', '日期', '售卖价',
+                    '实收金额', '销售量_含拒退', '销售量_不含拒退',
+                    '平台',
+                    '品牌', '成本', '季节', '商品年份']
+
+
+# 函数运行时间装饰器
+def use_time(func):
+    def wrapper(*args, **kwargs):
+        start = time()
+        result = func(*args, **kwargs)
+        use = round(time() - start, 3)
+        print('%s()用时: %s秒' % (func.__name__, use))
+        return result
+
+    return wrapper
+
+
+# 向 excel 插入图片
+def save_image_to_excel(file_path, picture_path, columns, sheet_index=0):
+    """
+    把图片插入到xlsx
+    :param file_path: 文件路径
+    :param picture_path: 图片路径
+    :param columns: 2D_list, [[0, B], [2, D]]表示: 依据第0列, 插入到到B列; 依据第2列, 插入到到D列
+    :param sheet_index: 选择sheet, 从0开现
+    :return: None
+    """
+    print('插入图片...')
+    # img_path = '//10.1.4.184/g/data/picture/X89113075049.png'
+    # wb = load_workbook(r'G:\yi\yi_code\hxfs_data_y\my_module\1.xlsx')
+    df = pd.read_excel(file_path, sheet_index=sheet_index)
+    wb = load_workbook(file_path)
+    ws = wb.worksheets[sheet_index]
+    for depend_col, insert_col in columns:
+        depend_list = df.iloc[:, depend_col].tolist()
+        for idx, pic_name in enumerate(depend_list, start=1):
+            try:
+                img = Image(os.path.join(picture_path, pic_name + '.jpg'))
+            except:
+                try:
+                    img = Image(os.path.join(picture_path, pic_name + '.png'))
+                except:
+                    continue
+            anchor = insert_col + str(idx + 1)
+            ws.add_image(img, anchor=anchor)
+    wb.save(file_path)
+    print('插入图片完成')
+
+
+def concat_files(folder):
+    """
+    读取文件夹内的所有表格, 合并成一个表
+    :param folder: 文件夹路径
+    :return: DataFrame
+    """
+    df_list = []
+    for fn in os.listdir(folder):
+        ffn = os.path.join(folder, fn)
+        if '.xlsx' not in ffn:
+            continue
+        # print(ffn)
+        df_temp = pd.read_excel(ffn)
+        df_list.append(df_temp)
+    df = pd.concat(df_list)
+    return df
+
+
+# ['货号', '商品名称', '尺码', '日期', '售卖价', '实收金额', '销售量_含拒退', '销售量_不含拒退']
+def read_sales_b():
+    """
+    ['款号颜色代码', '商品名称', '尺码', '日期', '售卖价', '活动价', '销售量_含拒退', '销售量_不含拒退']
+    """
+    df_b = concat_files(
+        './PlatformB'
+    )
+    df_b['实收金额'] = np.where(df_b['活动价'] == 0, df_b['售卖价'], df_b['活动价'])
+    df_b = df_b.rename(columns={'款号颜色代码': '货号'})
+    df_b = df_b.drop(columns=['活动价'])
+    return df_b
+
+
+@use_time
+def out_sales_summary_tb():
+    print('输出"2019全平台销售总表.xlsx"...')
+    df_a = concat_files('./PlatformA')
+    df_a['平台'] = '平台A'
+    df_b = read_sales_b()
+    df_b['平台'] = '平台B'
+    df_all = df_a.append(df_b)
+    # ['售卖价', '商品名称', '实收金额', '尺码', '平台',
+    # '日期', '货号', '销售量_不含拒退', '销售量_含拒退']
+    # print(df_all.head())
+    df_base = pd.read_excel(
+        '商品基础信息表.xlsx',
+        usecols=['货号', '品牌', '成本', '季节', '商品年份']
+    )
+    df_all = pd.merge(df_all, df_base, on='货号', how='left',
+                      validate='many_to_one')
+    df_all['日期'] = df_all['日期'].dt.date
+    # print(df_all.head())
+
+    df_all.to_excel('./data_out/2019全平台销售总表.xlsx', index=None)
+    # df_all.to_pickle('./data_out/2019全平台销售总表.pkl')
+    print('输出"2019全平台销售总表.xlsx"完成', end='\n**********\n')
+
+
+# 压缩图片
+@use_time
+def compress_image(src_path, dst_path, w=80, h=80):
+    print('压缩图片...')
+    src_fn_set = set(os.listdir(src_path))
+    dst_fn_set = set(os.listdir(dst_path))
+    fn_set = src_fn_set - dst_fn_set
+    if len(fn_set) == 0:
+        print('无可更新图片', end='\n**********\n')
+        return
+
+    from PIL import Image
+    for fn in fn_set:
+        src_ffn = os.path.join(src_path, fn)
+        dst_ffn = os.path.join(dst_path, fn)
+
+        larger_img = Image.open(src_ffn)
+        small_img = larger_img.resize((w, h), resample=Image.ANTIALIAS)
+        small_img.save(dst_ffn)
+
+        print(src_ffn)
+        print(dst_ffn)
+    print('压缩图片完成', end='\n**********\n')
+
+
+"""
+输出
+./data_out/2019销售汇总表.xlsx
+"""
+out_xlsx_title = ['货号', '商品名称', '图片', '总销量', '总销售额',
+                  '总成本', '总利润']
+
+
+@use_time
+def out_goods_id_total():
+    print('输出"2019销售汇总表.xlsx"...')
+    # df = pd.read_pickle('./data_out/2019全平台销售总表.pkl')
+    df = pd.read_excel('./data_out/2019全平台销售总表.xlsx')
+    # print(df.head())
+    df = df[['货号', '商品名称', '实收金额', '销售量_不含拒退', '成本']]
+    df = df.rename(columns={'销售量_不含拒退': '总销量'})
+    df['总销售额'] = df['实收金额'] * df['总销量']
+    df = pd.pivot_table(
+        df,
+        index=['货号', '商品名称', '成本'],
+        values=['总销量', '总销售额'],
+        aggfunc=sum)
+    df = df.reset_index()
+    df['总成本'] = df['总销量'] * df['成本']
+    df['总利润'] = df['总销售额'] - df['总成本']
+
+    total_series = df[['总销量', '总销售额', '总成本', '总利润']].sum(axis=0).reindex(out_xlsx_title)
+    total_series['货号'] = '合计'
+    # print(total_series)
+    # return
+    df = df.append(total_series, ignore_index=True)
+
+    df = df.reindex(columns=out_xlsx_title)
+    # print(df)
+    ffn = './data_out/2019销售汇总表.xlsx'
+    df.to_excel(ffn, index=None)
+    # 插入图片
+    picture_path = './压缩图'
+    save_image_to_excel(ffn, picture_path, [[0, 'C']])
+    print('输出"2019销售汇总表.xlsx"完成', end='\n**********\n')
+
+
+if __name__ == '__main__':
+    # 1: 压缩图片
+    compress_image('./原图', './压缩图')
+
+    # 2: 输出"2019全平台销售总表.xlsx"
+    out_sales_summary_tb()
+
+    # 3: 输出"2019销售汇总表.xlsx"
+    out_goods_id_total()

A002_pandas简介/A002.py

@@ -0,0 +1,5 @@
+import numpy as np
+
+a = np.array([[1, 2], [3, 4]])
+print(a)
+print(type(a))