def sandbox():
#set attributes for workbook
fnt = Font()
fnt.name, fnt.colour_index, fnt.bold, fnt._weight = 'Arial',0x08,False,0x0190
borders = Borders()
borders.left, borders.right, borders.top, borders.bottom = 0,0,0,0
al = Alignment()
al.horz, al.vert = Alignment.HORZ_CENTER,Alignment.VERT_CENTER
style = XFStyle()
style.font, style.borders,style.alignment = fnt,borders,al
# create wb instance
wb = Workbook()
#add a sheet for each csv file being imported to excel
s = util.GetFileListing('Note*.csv')
csv_files = s.sys_cmd.output
worksheet_titles = [ ':'.join(a_file.split(':')[1:-2]) for a_file in csv_files ]
ws_list = [ wb.add_sheet(ws_title) for ws_title in worksheet_titles ]
F = util.FileEdit(csv_titles)
for ws,f in zip(ws_list,F.file_utils):
a_list = [ a_row.rstrip().split(',') for a_row in f.contents ]
for a_row,a_line in enumerate(a_list):
for a_col,a_cell in enumerate(a_line): ws.write(a_row,a_col,a_cell,style)
wb.save('chk_out.xls')
def write_excel(results):
title = ['DATE', 'User ID', 'SCREEN NAME', 'Fans', 'Fan Growth', 'Fan Growth %', 'Tweets', 'Retweets', 'Comments', 'direct @',
'Likes', 'Impression', 'ER 30 days', 'ER 7 days', '#1 Post URL', '#1 Post ER', '#1 Post RT', '#1 Post CT', '#2 Post URL',
'#2 Post ER', '#2 Post RT', '#2 Post CT', '#3 Post URL', '#3 Post ER', '#3 Post RT', '#3 Post CT', '#4 Post URL',
'#4 Post ER', '#4 Post RT', '#4 Post CT', '#5 Post URL', '#5 Post ER', '#5 Post RT', '#5 Post CT', '#1 Influencer URL',
'#1 Influencer Tweets Count', '#1 Influencer Comments Count', '#1 Influencer Direct @ Count', '#2 Influencer URL',
'#2 Influencer Tweets Count', '#2 Influencer Comments', '#2 Influencer Direct @ Count', '#3 Influencer URL',
'#3 Influencer Tweets Count', '#3 Influencer Comments', '#3 Influencer Direct @ Count', '#4 Influencer URL',
'#4 Influencer Tweets Count', '#4 Influencer Comments', '#4 Influencer Direct @ Count', '#5 Influencer URL',
'#5 Influencer Tweets Count', '#5 Influencer Comments', '#5 Influencer Direct @ Count', '#1 Hashtag',
"#1 Hashtag's engagement rate", '#2 Hashtag', "#2 Hashtag's engagement rate", '#3 Hashtag',
"#3 Hashtag's engagement rate", 'Question Posted', 'Question Responded', 'Question Response Time', 'Response Share']
w = Workbook()
ws = w.add_sheet('Weekly Raw Data')
wt = w.add_sheet('Fans Info')
font = Font()
font.height = 12 * 0x14
font.name = str_to_unicode('微软雅黑')
title_style = Style.XFStyle()
title_style.font = font
fontbold = Font()
fontbold.height = 12 * 0x14
fontbold.bold = True
fontbold.name = str_to_unicode('微软雅黑')
boldstyle = Style.XFStyle()
boldstyle.font = fontbold
percent = Style.XFStyle()
percent.font = font
percent.num_format_str = '0.00%'
for i in range(len(title)):
ws.col(i).width = 3600
ws.write_cols(0, 0, title, title_style)
abscissa = 0
for res in range(len(results)):
screen_name, uid, day, period, fans, fan_growth, tweets, retweets, comments, direct_at, likes, impressions, \
er_30, er_7, response_share, top_posts, top_influencer, top_hashtag, questions, responds, mean_res, active, interactive, \
verified, subfans, province, gender, age, tag, fans_week, fans_hour, brand_week, brand_hour = results[res]
fan_percent = fan_growth / float(fans - fan_growth)
top_posts, top_influencer, top_hashtag, verified, subfans, province, gender, age, tag, fans_week, \
fans_hour, brand_week, brand_hour = [format_data(p) for p in (top_posts, top_influencer, top_hashtag, \
verified, subfans, province, gender, age, tag, fans_week, \
fans_hour, brand_week, brand_hour)]
mean_res = round(mean_res/60.0, 2)
#print res
t_posts = []
top_posts = sorted(top_posts, key=lambda x:x[0], reverse=True)
for post in top_posts:
t_posts.extend([post[1]['url'], post[0], post[1]['nret'], post[1]['ncmt']])
t_posts.extend(['N/A'] * (20 - len(t_posts)))
t_influencer = []
top_influencer = sorted(top_influencer, key=lambda x:x[0], reverse=True)
for influ in top_influencer:
weibourl = 'http://weibo.com/u/%s'%influ[1]['uid']
t_influencer.extend([weibourl, influ[1].get('reposts', 0), influ[1].get('comments', 0), influ[1].get('direct_at', 0)])
t_influencer.extend(['N/A'] * (20 - len(t_influencer)))
t_hashtag = []
if top_hashtag:
top_hashtag = sorted(top_hashtag, key=lambda x:x[0], reverse=True)
[t_hashtag.extend([hash[1], hash[0]]) for hash in top_hashtag]
t_hashtag.extend(['N/A'] * (6 - len(t_hashtag)))
account_index = [day.strftime('%Y-%m-%d'), uid, screen_name, fans, fan_growth, fan_percent, tweets, retweets, \
comments, direct_at, likes if likes else 0, \
impressions, er_30, er_7] + t_posts + t_influencer + t_hashtag + [questions, responds, mean_res,
response_share if response_share else 'N/A']
#将第一页数据写入execl
ws.write_cols(res+1, 0, account_index, title_style)
tag.extend([('N/A', 0) for i in range(10 - len(tag))])
province.extend([('N/A', 0) for i in range(10 - len(province))])
subfans.extend([0 for i in range(12 - len(subfans))])
vertical_title = [screen_name, 'Active', 'Active Fans', 'Other Fans', '', 'Interaction', 'Interactive Fans', 'Other Fans', '', 'Verified Type', \
'Verified', 'Daren', 'Un-verified', '', 'Fan Number', '0~9', '10~49', '50~99', '100~199', '200~299', '300~399', '400~499',\
'500~999', '1000~1999', '2000~4999', '5000~9999', '>=10000', '', 'Gender', 'Male', 'Female', '', 'Age', '<18', '18~24', \
'25~29', '30~34', '35~39', '40~49', '50~59', '>=60', '', 'Tag'] + [i[0] for i in tag] + ['', 'Province'] + \
[str_to_unicode(provincesdict.get(str(i[0]), '')) for i in province]+ ['', 'Hour', '0-1', '1-2', '2-3', '3-4', '4-5', '5-6',\
'6-7', '7-8', '8-9', '9-10', '10-11', '11-12', '12-13', '13-14', '14-15', '15-16', '16-17', '17-18', '18-19', '19-20', '20-21', '21-22', \
'22-23', '23-0', '', 'Days', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday', '']
wt.col(res*3).width = 4000
ordinate = 0
for ver in range(len(vertical_title)):
if ver in (0, 1) or not vertical_title[ver-1]:
wt.write(ordinate, abscissa, vertical_title[ver], boldstyle)
else:
wt.write(ordinate, abscissa, vertical_title[ver], title_style)
ordinate += 1
if verified:
verified_count = float(sum(verified))
verified_type = [verified[1]/verified_count, verified[2]/verified_count, verified[0]/verified_count] if verified_count > 0 else [0, 0, 0]
else:
verified_type = [0] * 3
if len(gender)!=2: gender = [0, 0]
else:
gender.sort()
gender = [gender[1][1], gender[0][1]]
tagdata = [i[1] for i in tag]
provincedata = [i[1] for i in province]
if age:
age = [i[1] for i in sorted(age.items())]
age_type = [i/float(sum(age)) for i in age]
else:
age_type = [0] * 8
if not brand_hour : brand_hour = [0] * 24
if not brand_week : brand_week = [0] * 7
subfans_type, gender_type, tag_type, province_type, fanshour_type, fansweek_type, brandhour_type, brandweek_type = \
[div_data(j) for j in [subfans, gender, tagdata, provincedata, fans_hour, fans_week, brand_hour, brand_week]]
gaps = ['', 'Percentage']
vertical_data = ['', 'Percentage', active, 1-active if active else 0, '', 'Percentage', interactive, 1-interactive if interactive else 0, \
'', 'Percentage'] + verified_type + gaps + subfans_type + gaps + gender_type + gaps + age_type + gaps + \
tag_type + gaps + province_type + ['', 'Fans Activity'] + fanshour_type + ['', 'Fans Activity'] + fansweek_type
wt.col(res*3+1).width = 4000
ordinate = 0
abscissa += 1
for ver in range(len(vertical_data)):
if ver in (0, 1) or not vertical_title[ver-1]:
wt.write(ordinate, abscissa, vertical_data[ver], boldstyle)
else:
wt.write(ordinate, abscissa, vertical_data[ver], percent)
ordinate += 1
wt.col(res*3+2).width = 4000
ordinate = 0
rest_data = [''] * 66 + ['Brand Activity'] + brandhour_type + ['', 'Brand Activity'] + brandweek_type
abscissa += 1
for ver in range(len(rest_data)):
if ver in (0, 1) or not vertical_title[ver-1]:
wt.write(ordinate, abscissa, rest_data[ver], boldstyle)
else:
wt.write(ordinate, abscissa, rest_data[ver], percent)
ordinate += 1
abscissa += 2
return w
def write_excel(results):
title = [
'DATE', 'User ID', 'SCREEN NAME', 'Fans', 'Fan Growth', 'Fan Growth %',
'Tweets', 'Retweets', 'Comments', 'direct @', 'Likes', 'Impression',
'ER 30 days', 'ER 7 days', '#1 Post URL', '#1 Post ER', '#1 Post RT',
'#1 Post CT', '#2 Post URL', '#2 Post ER', '#2 Post RT', '#2 Post CT',
'#3 Post URL', '#3 Post ER', '#3 Post RT', '#3 Post CT', '#4 Post URL',
'#4 Post ER', '#4 Post RT', '#4 Post CT', '#5 Post URL', '#5 Post ER',
'#5 Post RT', '#5 Post CT', '#1 Influencer URL',
'#1 Influencer Tweets Count', '#1 Influencer Comments Count',
'#1 Influencer Direct @ Count', '#2 Influencer URL',
'#2 Influencer Tweets Count', '#2 Influencer Comments',
'#2 Influencer Direct @ Count', '#3 Influencer URL',
'#3 Influencer Tweets Count', '#3 Influencer Comments',
'#3 Influencer Direct @ Count', '#4 Influencer URL',
'#4 Influencer Tweets Count', '#4 Influencer Comments',
'#4 Influencer Direct @ Count', '#5 Influencer URL',
'#5 Influencer Tweets Count', '#5 Influencer Comments',
'#5 Influencer Direct @ Count', '#1 Hashtag',
"#1 Hashtag's engagement rate", '#2 Hashtag',
"#2 Hashtag's engagement rate", '#3 Hashtag',
"#3 Hashtag's engagement rate", 'Question Posted',
'Question Responded', 'Question Response Time', 'Response Share'
]
w = Workbook()
ws = w.add_sheet('Weekly Raw Data')
wt = w.add_sheet('Fans Info')
font = Font()
font.height = 12 * 0x14
font.name = str_to_unicode('微软雅黑')
title_style = Style.XFStyle()
title_style.font = font
fontbold = Font()
fontbold.height = 12 * 0x14
fontbold.bold = True
fontbold.name = str_to_unicode('微软雅黑')
boldstyle = Style.XFStyle()
boldstyle.font = fontbold
percent = Style.XFStyle()
percent.font = font
percent.num_format_str = '0.00%'
for i in range(len(title)):
ws.col(i).width = 3600
ws.write_cols(0, 0, title, title_style)
abscissa = 0
for res in range(len(results)):
screen_name, uid, day, period, fans, fan_growth, tweets, retweets, comments, direct_at, likes, impressions, \
er_30, er_7, response_share, top_posts, top_influencer, top_hashtag, questions, responds, mean_res, active, interactive, \
verified, subfans, province, gender, age, tag, fans_week, fans_hour, brand_week, brand_hour = results[res]
fan_percent = fan_growth / float(fans - fan_growth)
top_posts, top_influencer, top_hashtag, verified, subfans, province, gender, age, tag, fans_week, \
fans_hour, brand_week, brand_hour = [format_data(p) for p in (top_posts, top_influencer, top_hashtag, \
verified, subfans, province, gender, age, tag, fans_week, \
fans_hour, brand_week, brand_hour)]
mean_res = round(mean_res / 60.0, 2)
#print res
t_posts = []
top_posts = sorted(top_posts, key=lambda x: x[0], reverse=True)
for post in top_posts:
t_posts.extend(
[post[1]['url'], post[0], post[1]['nret'], post[1]['ncmt']])
t_posts.extend(['N/A'] * (20 - len(t_posts)))
t_influencer = []
top_influencer = sorted(top_influencer,
key=lambda x: x[0],
reverse=True)
for influ in top_influencer:
weibourl = 'http://weibo.com/u/%s' % influ[1]['uid']
t_influencer.extend([
weibourl, influ[1].get('reposts', 0),
influ[1].get('comments', 0), influ[1].get('direct_at', 0)
])
t_influencer.extend(['N/A'] * (20 - len(t_influencer)))
t_hashtag = []
if top_hashtag:
top_hashtag = sorted(top_hashtag, key=lambda x: x[0], reverse=True)
[t_hashtag.extend([hash[1], hash[0]]) for hash in top_hashtag]
t_hashtag.extend(['N/A'] * (6 - len(t_hashtag)))
account_index = [day.strftime('%Y-%m-%d'), uid, screen_name, fans, fan_growth, fan_percent, tweets, retweets, \
comments, direct_at, likes if likes else 0, \
impressions, er_30, er_7] + t_posts + t_influencer + t_hashtag + [questions, responds, mean_res,
response_share if response_share else 'N/A']
#将第一页数据写入execl
ws.write_cols(res + 1, 0, account_index, title_style)
tag.extend([('N/A', 0) for i in range(10 - len(tag))])
province.extend([('N/A', 0) for i in range(10 - len(province))])
subfans.extend([0 for i in range(12 - len(subfans))])
vertical_title = [screen_name, 'Active', 'Active Fans', 'Other Fans', '', 'Interaction', 'Interactive Fans', 'Other Fans', '', 'Verified Type', \
'Verified', 'Daren', 'Un-verified', '', 'Fan Number', '0~9', '10~49', '50~99', '100~199', '200~299', '300~399', '400~499',\
'500~999', '1000~1999', '2000~4999', '5000~9999', '>=10000', '', 'Gender', 'Male', 'Female', '', 'Age', '<18', '18~24', \
'25~29', '30~34', '35~39', '40~49', '50~59', '>=60', '', 'Tag'] + [i[0] for i in tag] + ['', 'Province'] + \
[str_to_unicode(provincesdict.get(str(i[0]), '')) for i in province]+ ['', 'Hour', '0-1', '1-2', '2-3', '3-4', '4-5', '5-6',\
'6-7', '7-8', '8-9', '9-10', '10-11', '11-12', '12-13', '13-14', '14-15', '15-16', '16-17', '17-18', '18-19', '19-20', '20-21', '21-22', \
'22-23', '23-0', '', 'Days', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday', '']
wt.col(res * 3).width = 4000
ordinate = 0
for ver in range(len(vertical_title)):
if ver in (0, 1) or not vertical_title[ver - 1]:
wt.write(ordinate, abscissa, vertical_title[ver], boldstyle)
else:
wt.write(ordinate, abscissa, vertical_title[ver], title_style)
ordinate += 1
if verified:
verified_count = float(sum(verified))
verified_type = [
verified[1] / verified_count, verified[2] /
verified_count, verified[0] / verified_count
] if verified_count > 0 else [0, 0, 0]
else:
verified_type = [0] * 3
if len(gender) != 2: gender = [0, 0]
else:
gender.sort()
gender = [gender[1][1], gender[0][1]]
tagdata = [i[1] for i in tag]
provincedata = [i[1] for i in province]
if age:
age = [i[1] for i in sorted(age.items())]
age_type = [i / float(sum(age)) for i in age]
else:
age_type = [0] * 8
if not brand_hour: brand_hour = [0] * 24
if not brand_week: brand_week = [0] * 7
subfans_type, gender_type, tag_type, province_type, fanshour_type, fansweek_type, brandhour_type, brandweek_type = \
[div_data(j) for j in [subfans, gender, tagdata, provincedata, fans_hour, fans_week, brand_hour, brand_week]]
gaps = ['', 'Percentage']
vertical_data = ['', 'Percentage', active, 1-active if active else 0, '', 'Percentage', interactive, 1-interactive if interactive else 0, \
'', 'Percentage'] + verified_type + gaps + subfans_type + gaps + gender_type + gaps + age_type + gaps + \
tag_type + gaps + province_type + ['', 'Fans Activity'] + fanshour_type + ['', 'Fans Activity'] + fansweek_type
wt.col(res * 3 + 1).width = 4000
ordinate = 0
abscissa += 1
for ver in range(len(vertical_data)):
if ver in (0, 1) or not vertical_title[ver - 1]:
wt.write(ordinate, abscissa, vertical_data[ver], boldstyle)
else:
wt.write(ordinate, abscissa, vertical_data[ver], percent)
ordinate += 1
wt.col(res * 3 + 2).width = 4000
ordinate = 0
rest_data = [''] * 66 + ['Brand Activity'] + brandhour_type + [
'', 'Brand Activity'
] + brandweek_type
abscissa += 1
for ver in range(len(rest_data)):
if ver in (0, 1) or not vertical_title[ver - 1]:
wt.write(ordinate, abscissa, rest_data[ver], boldstyle)
else:
wt.write(ordinate, abscissa, rest_data[ver], percent)
ordinate += 1
abscissa += 2
return w
