Example #1
0
def run2():
    try:
        # 读取数据
        df = du_old_excel('充值')
        df2 = du_excel('注册16')
        df3 = du_excel('注册30')
    except FileNotFoundError:
        print('\n缺少运行数据,请先下载……')
        exit()

    df3 = df2.append(df3, ignore_index=True)

    # 提取充值数据的日期
    df['day'] = df['pay_time'].apply(lambda x: x.split(' ')[0].split('/')[2])
    df['on'] = df['player_id'].apply(lambda x: str(x)) + '|' + df['day']

    # # 整理前2天当日的注册数据
    df3['Flag'] = 'new'
    df3.rename(columns={'用户ID': 'player_id'}, inplace=True)
    df3['day'] = df3['注册时间'].apply(lambda x: x.split(' ')[0].split('/')[2])
    df3['on'] = df3['player_id'].apply(lambda x: str(x)) + '|' + df3['day']
    df3 = df3[['on', 'Flag']]

    df = pd.merge(left=df, right=df3, on='on', how='left')
    df['Flag'].fillna('old', inplace=True)

    i = 0
    df_form = pd.DataFrame()

    def df_f(df):

        # 人数计算
        df_form.loc[i, '新用户量'] = len(df[df['Flag'] == 'new']['player_id'].unique())
        df_form.loc[i, '总用户量'] = len(df['player_id'].unique())
        df_form.loc[i, '新用户占比'] = '%.2f%%' % (df_form.loc[i, '新用户量'] / df_form.loc[i, '总用户量'] * 100)

        # 金额消费计算
        df_form.loc[i, '新用户消费金额'] = df[df['Flag'] == 'new']['amount'].sum()
        df_form.loc[i, '总消费'] = df['amount'].sum()
        df_form.loc[i, '新用户消费占比'] = '%.2f%%' % (df_form.loc[i, '新用户消费金额'] / df_form.loc[i, '总消费'] * 100)

        return df_form

    df_form = df_f(df)

    # 删除多余2列
    del df_form['总用户量']
    del df_form['总消费']

    print('第二个表运行完毕.')

    return df_form
Example #2
0
def run4():
    df = du_excel('红宝石')
    df2 = du_excel('红宝石明细')

    '----------------------计算第一个表----------------------------------------------------------'

    df = pd.pivot_table(df, values='数值', index='时间', columns='原因')
    df.reset_index(inplace=True)

    df = df[
        ['时间', '游戏产出', '新手礼包', '充值礼包', '成就任务', '分享抽奖', '玩家兑换红包', '玩家兑换话费', '玩家兑换金币', '幸运抽奖', '购买物品', '欢乐夺宝']]

    df = pd.DataFrame(df.sum()).T

    '================================计算第二个表========================================='

    def fx(x):
        if x < 10:
            return '第一档'
        elif (x >= 10) and (x < 80):
            return '第二档'
        else:
            return '第三档'

    df2['档位'] = df2['游戏产出红宝石(红包场)'].apply(lambda x: fx(x))

    df2 = df2.groupby('档位').sum()
    df2 = df2[['次数', '总额']].T

    def hongbaoshi_minxi(df2):
        df2['总和'] = df2.apply(lambda x: x.sum(), axis=1)

        df2['一档比'] = (df2['第一档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))
        df2['二档比'] = (df2['第二档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))
        df2['三档比'] = (df2['第三档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))

        df2 = df2[['第一档', '第二档', '第三档', '一档比', '二档比', '三档比', '总和']]
        df2.reset_index(inplace=True)

        return df2

    df2 = hongbaoshi_minxi(df2)

    print('第四个表运行完毕.')

    return df, df2
Example #3
0
def run3():
    try:
        # 读取数据
        df = du_excel('金币')
        df_map = pd.read_excel('C:\\Users\Administrator\Desktop\map.xlsx')
    except FileNotFoundError:
        print('\n缺少运行数据,请先下载……')
        exit()

    df3 = df[df.columns[:3]]
    df3.dropna(axis=0, how='any', inplace=True)
    df3 = pd.pivot_table(df3, values='数值', index='时间', columns='原因')
    df3 = df3[['每日登录抽奖', 'VIP奖励', '新手礼包', '成就任务', '分享抽奖']]

    df3.reset_index(inplace=True)

    df3=pd.DataFrame(df3.sum()).T


    '-----------------金币消耗汇总表--------------'

    # 金币消耗-透视
    df2 = df[df.columns[-3:]]
    df2.dropna(axis=0, how='any', inplace=True)
    df2 = pd.pivot_table(df2, values='数值2', index='时间2', columns='原因2')
    del df2['单局结算']
    df2.reset_index(drop=True,inplace=True)

    df2 = pd.DataFrame(df2.sum()).T


    '----------------------------金币产出汇总表--------------------------'
    # 金币产出-透视
    df = df[df.columns[:3]]
    df_map = df_map[['原因', 'jinbi']]
    df_map.dropna(inplace=True)

    # 合并匹配表
    df = pd.merge(left=df, right=df_map, on='原因', how='left')

    df = df.groupby(['时间', 'jinbi'])['数值'].sum()

    df = pd.DataFrame(df)
    df.reset_index(inplace=True)

    df = pd.pivot_table(df, values='数值', index='时间', columns='jinbi')

    df.reset_index(inplace=True)

    df = df[['时间', '用户充值', '系统赠送', '兑换红宝石', '兑换鱼雷', '领取邮件']]

    df.reset_index(drop=True, inplace=True)

    df = pd.DataFrame(df.sum()).T

    print('第三个表运行完毕.')

    return df, df2, df3
Example #4
0
def run9():
    df = du_excel('渠道')

    df = df.groupby('时间').sum()
    del df['充值人数']
    del df['最高在线']
    del df['付费用户占比']

    df.reset_index(inplace=True)

    df.loc[0, '兑换总金额'] = df.loc[0, '兑换红包金额'] + df.loc[0, '兑换话费金额']
    del df['兑换话费金额']
    del df['兑换红包金额']

    # print(df)

    print('\n第九个表【渠道】运行完毕……')

    return df
Example #5
0
def run7():
    df = du_excel('税收')

    # 选取7天之前的时间
    df = df[df['日期'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]

    df['差值'] = df['税收'] - df['税收'].shift(24)

    df = df.tail(4)

    df = pd.pivot_table(df, values='差值', index='日期', columns='场')

    df['总和'] = df.apply(lambda x: x.sum(), axis=1)

    df.rename(columns={'猜猜乐场': '猜猜乐'}, inplace=True)

    df = df[['红包场', '鱼雷场', '水果场', '猜猜乐', '总和']]

    print('第七个表【税收】运行完毕……')

    return df
Example #6
0
def run3():

    df = du_excel('金币分类')
    df_map = pd.read_excel('C:\\Users\Administrator\Desktop\map.xlsx')


    # 修改不规则的列
    for x in range(df.shape[0]):
        if '鱼雷' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换鱼雷'

        elif '红包券' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换红包券'

        elif '迎新红包' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换迎新红包'

    def change_col(x):
        if '鱼雷' in x:
            return int(x.split('(')[0])
        elif '红包券' in x:
            return int(x.split('(')[0])
        elif '迎新红包' in x:
            return int(x.split('(')[0])
        else:
            return int(x)

    df['数值'] = df['数值'].apply(lambda x: change_col(str(x)))

    '-----------系统赠送金币分类---------------------'
    df3 = df[df.columns[:3]]
    df3.dropna(axis=0, how='any', inplace=True)

    df3 = pd.pivot_table(df3, values='数值', index='时间', columns='原因')

    df3 = df3[['每日登录抽奖', 'VIP奖励', '新手礼包', '成就任务']]
    df3.reset_index(inplace=True)
    df3 = df3[df3['时间'] >= pd.to_datetime('{}'.format(bef_yesterday))]

    df3['时间'] = df3['时间'].apply(lambda x: str(x)[:10])



    '-----------------金币消耗汇总表--------------'

    # 金币消耗-透视
    df2 = df[df.columns[-3:]]
    df2.dropna(axis=0, how='any', inplace=True)
    df2 = pd.pivot_table(df2, values='数值2', index='时间2', columns='原因2')
    del df2['单局结算']
    df2.reset_index(inplace=True)
    df2['时间2'] = df2['时间2'].apply(lambda x: str(x)[:10])


    '----------------------------金币产出汇总表--------------------------'
    # 金币产出-透视
    df = df[df.columns[:3]]
    df_map = df_map[['原因', 'jinbi']]
    df_map.dropna(inplace=True)

    # 合并匹配表
    df = pd.merge(left=df, right=df_map, on='原因', how='left')

    df = df.groupby(['时间', 'jinbi'])['数值'].sum()

    df = pd.DataFrame(df)
    df.reset_index(inplace=True)


    df = pd.pivot_table(df, values='数值', index='时间', columns='jinbi')

    df.reset_index(inplace=True)


    # 这里兑换礼物需要修改 '兑换红宝石','兑换鱼雷'
    df = df[['时间', '用户充值', '系统赠送', '兑换红包券','兑换鱼雷','兑换迎新红包', '领取邮件']]
    df['时间'] = df['时间'].apply(lambda x: str(x)[:10])

    print('\n第三个表运行完毕……')

    return df, df2, df3
Example #7
0
def run4():
    df = du_excel('红宝石')
    df2 = du_excel('红宝石明细')

    # 修改不规则的列=====================================
    for x in range(df.shape[0]):
        if '红包' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换红包'

        elif '话费' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换话费'

        elif '金币' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换金币'

    def change_col(x):
        if '红包' in x:
            return int(x.split('(')[0])
        elif '话费' in x:
            return int(x.split('(')[0])
        elif '金币' in x:
            return int(x.split('(')[0])
        else:
            return int(x)

    df['数值'] = df['数值'].apply(lambda x: change_col(str(x)))

    # 选取7天之前的时间
    df = df[df['时间'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]
    df2 = df2[
        df2['日期'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]

    # ==========================================================

    '----------------------计算第一个表----------------------------------------------------------'

    df = pd.pivot_table(df, values='数值', index='时间', columns='原因')
    df.reset_index(inplace=True)

    # df = df[
    #     ['时间', '游戏产出', '新手礼包', '充值礼包', '玩家兑换红包', '玩家兑换金币', '幸运抽奖', '购买物品', '欢乐夺宝','活动抽奖']]

    df = df[[
        '时间', '游戏产出', '新手礼包', '充值礼包', '玩家兑换红包', '玩家兑换金币', '幸运抽奖', '购买物品',
        '欢乐夺宝', '分享抽奖'
    ]]

    df = pd.DataFrame(df.sum()).T

    '================================计算第二个表========================================='

    def fx(x):
        if x < 10:
            return '第一档'
        elif (x >= 10) and (x < 80):
            return '第二档'
        else:
            return '第三档'

    df2['档位'] = df2['游戏产出红宝石(红包场)'].apply(lambda x: fx(x))

    df2 = df2.groupby('档位').sum()
    df2 = df2[['次数', '总额']].T

    def hongbaoshi_minxi(df2):
        df2['总和'] = df2.apply(lambda x: x.sum(), axis=1)

        df2['一档比'] = (df2['第一档'] /
                      df2['总和']).apply(lambda x: '%.2f%%' % (x * 100))
        df2['二档比'] = (df2['第二档'] /
                      df2['总和']).apply(lambda x: '%.2f%%' % (x * 100))
        df2['三档比'] = (df2['第三档'] /
                      df2['总和']).apply(lambda x: '%.2f%%' % (x * 100))

        df2 = df2[['第一档', '第二档', '第三档', '一档比', '二档比', '三档比', '总和']]
        df2.reset_index(inplace=True)

        return df2

    df2 = hongbaoshi_minxi(df2)

    del df2['一档比']
    del df2['二档比']
    del df2['三档比']

    print('第四个表运行完毕.')

    return df, df2
Example #8
0
def run3():
    df = du_excel('金币分类')
    df_map = pd.read_excel('C:\\Users\Administrator\Desktop\map.xlsx')

    # 修改不规则的列====================================
    for x in range(df.shape[0]):
        if '鱼雷' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换鱼雷'

        elif '红包券' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换红包券'
        elif '迎新红包' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '兑换迎新红包'

    def change_col(x):
        if '鱼雷' in x:
            return int(x.split('(')[0])
        elif '红包券' in x:
            return int(x.split('(')[0])
        elif '迎新红包' in x:
            return int(x.split('(')[0])
        else:
            return int(x)

    df['数值'] = df['数值'].apply(lambda x: change_col(str(x)))

    # ====================================================

    df3 = df[df.columns[:3]]
    df3.dropna(axis=0, how='any', inplace=True)

    # 选取7天之前的时间
    df3 = df3[
        df3['时间'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]
    print('\n如果是月报,需要修改! func中的y7值改为30\n')

    df3 = pd.pivot_table(df3, values='数值', index='时间', columns='原因')

    df3 = df3[['每日登录抽奖', 'VIP奖励', '新手礼包', '成就任务']]

    df3.reset_index(inplace=True)

    df3 = pd.DataFrame(df3.sum()).T

    '-----------------金币消耗汇总表--------------'

    # 金币消耗-透视
    df2 = df[df.columns[-3:]]
    df2.dropna(axis=0, how='any', inplace=True)

    # 选取7天之前的时间
    df2 = df2[
        df2['时间2'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]

    df2 = pd.pivot_table(df2, values='数值2', index='时间2', columns='原因2')
    del df2['单局结算']
    df2.reset_index(drop=True, inplace=True)

    df2 = pd.DataFrame(df2.sum()).T

    '----------------------------金币产出汇总表--------------------------'
    # 金币产出-透视
    df = df[df.columns[:3]]

    # 选取7天之前的时间
    df = df[df['时间'].apply(lambda x: pd.to_datetime(x)) >= pd.to_datetime(y7)]

    df_map = df_map[['原因', 'jinbi']]
    df_map.dropna(inplace=True)

    # 合并匹配表
    df = pd.merge(left=df, right=df_map, on='原因', how='left')

    df = df.groupby(['时间', 'jinbi'])['数值'].sum()

    df = pd.DataFrame(df)
    df.reset_index(inplace=True)

    df = pd.pivot_table(df, values='数值', index='时间', columns='jinbi')

    df.reset_index(inplace=True)

    df = df[['时间', '用户充值', '系统赠送', '兑换红包券', '兑换鱼雷', '兑换迎新红包', '领取邮件']]

    df.reset_index(drop=True, inplace=True)

    df = pd.DataFrame(df.sum()).T

    print('第三个表运行完毕.')

    return df, df2, df3
Example #9
0
def run4():

    df = du_excel('红宝石')
    df2 = du_excel('红宝石明细')



    # 修改不规则的列
    for x in range(df.shape[0]):
        if '红包' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换红包'

        elif '话费' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换话费'

        elif '金币' in str(df.loc[x, '数值']):
            df.loc[x, '原因'] = '玩家兑换金币'

    def change_col(x):
        if '红包' in x:
            return int(x.split('(')[0])
        elif '话费' in x:
            return int(x.split('(')[0])
        elif '金币' in x:
            return int(x.split('(')[0])
        else:
            return int(x)

    df['数值'] = df['数值'].apply(lambda x: change_col(str(x)))


    '----------------------计算第一个表----------------------------------------------------------'

    df = pd.pivot_table(df, values='数值', index='时间', columns='原因')
    df.reset_index(inplace=True)

    df = df[
        ['时间', '游戏产出', '新手礼包', '充值礼包', '成就任务',  '玩家兑换红包', '玩家兑换话费', '玩家兑换金币', '幸运抽奖', '购买物品', '欢乐夺宝']]

    df = df[df['时间'] >= pd.to_datetime('{}'.format(bef_yesterday))]

    df['时间'] = df['时间'].apply(lambda x: str(x)[:10])

    '================================计算第二个表========================================='


    def fx(x):
        if x < 10:
            return '第一档'
        elif (x >= 10) and (x < 80):
            return '第二档'
        else:
            return '第三档'


    df2['档位'] = df2['游戏产出红宝石(红包场)'].apply(lambda x: fx(x))


    def hongbaoshi_minxi(df2, value):
        df2 = pd.pivot_table(df2, values=value, index='日期', columns='档位', aggfunc=np.sum)
        df2['总和'] = df2.apply(lambda x: x.sum(), axis=1)

        # df2['一档比'] = (df2['第一档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))
        # df2['二档比'] = (df2['第二档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))
        # df2['三档比'] = (df2['第三档'] / df2['总和']).apply(lambda x: '%.2f%%' % (x*100))

        # df2 = df2[['第一档', '第二档', '第三档', '一档比', '二档比', '三档比', '总和']]

        df2 = df2[['第一档', '第二档', '第三档', '总和']]
        df2.reset_index(inplace=True)

        return df2


    df_ren = hongbaoshi_minxi(df2, '次数')

    df_money = hongbaoshi_minxi(df2, '总额')

    df2 = df_ren.append(df_money)


    df2 = df2[df2['日期'] >= pd.to_datetime('{}'.format(bef_yesterday))]
    df2['日期'] = df2['日期'].apply(lambda x: str(x)[:10])
    print('\n第四个表运行完毕……')

    return df, df2