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viewer.py
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from pandas import Series, DataFrame, read_pickle
import time
import matplotlib.pyplot as plt
from types import MethodType
def select_time(s, start_time, end_time):
if start_time == 'default':
start_timestamp = s.index[0]
else:
try:
start_timestamp = time.mktime(
time.strptime(start_time, "%Y-%m-%d %H:%M"))
except ValueError:
print(
'！！起始日期格式错误！！，应为 \'YYYY-mm-dd MM:HH\' 如 \'2020-05-05 15:05\'\n**已默认从第一条数据开始**\n')
start_timestamp = s.index[0]
# 处理start_time参数
if end_time == 'default':
end_timestamp = s.index[-1]
else:
try:
end_timestamp = time.mktime(
time.strptime(end_time, "%Y-%m-%d %H:%M"))
except ValueError:
print(
'！！截止日期格式错误！！，应为 \'YYYY-mm-dd MM:HH\' 如\'2020-05-05 15:05\'\n**已默认最后一条数据截止**\n')
end_timestamp = s.index[-1]
# 对series进行切片（选定的时间段）
return s[(s.index >= start_timestamp) & (s.index <= end_timestamp)]
def prep_plt(kinds):
kinds_len = len(kinds)
if kinds_len == 1:
sub_row = 1
sub_col = 1
fig = plt.figure(figsize=(12, 6), facecolor='w')
elif kinds_len == 2:
sub_row = 1
sub_col = 2
fig = plt.figure(figsize=(18, 6), facecolor='w')
elif (kinds_len == 3 or kinds_len == 4):
sub_row = 2
sub_col = 2
fig = plt.figure(figsize=(18, 12), facecolor='w')
elif (kinds_len == 5 or kinds_len == 6):
sub_row = 2
sub_col = 3
fig = plt.figure(figsize=(24, 16), facecolor='w')
elif kinds_len == 7:
sub_row = 3
sub_col = 3
fig = plt.figure(figsize=(24, 24), facecolor='w')
else:
print('error')
return sub_row, sub_col, fig
def sort_by(s, k, av):
ls = []
for i in s.index:
d = dict(time=i)
for j in range(len(s[i])):
# display(s[i])
row_av = s[i].iloc[j, 0]
row_data = int(s[i].iloc[j][k])
d.update({row_av: row_data})
# print(d)
ls.append(d)
# print(ls)
df = DataFrame(ls)
df.set_index(['time'], inplace=True)
if av != 'all':
df = df[av]
return df
def plt_line(df, title, fig, sub_row, sub_col, t):
ax = fig.add_subplot(sub_row, sub_col, t)
df.plot(ax=ax)
ax.grid()
strtime = []
for i in ax.get_xticks():
strtime.append(time.strftime("%m/%d\n%H:%M", time.localtime(i)))
ax.set_xticklabels(strtime)
ax.set_title(title)
def plt_bar(df, title, fig, sub_row, sub_col, t):
ax = fig.add_subplot(sub_row, sub_col, t)
df.plot(kind='bar', ax=ax)
ax.grid()
#strtime = []
# for i in ax.get_xticks():
# strtime.append(time.strftime("%m/%d\n%H:%M",time.localtime(i)))
# ax.set_xticklabels(strtime)
ax.set_title(title)
def get_interval(df, interval):
interval_df = DataFrame()
first = df.index[0]
last = df.index[-1]
start = first
end = start
while(end <= last):
end = start + interval
if df[(df.index >= start) & (df.index <= end)].empty: # 循环的最后一次有可能切片为空
break
t_df = df[(df.index >= start) & (df.index <= end)]
# print(t_df.index)
time_str = time.strftime(
"%m/%d\n%H:%M", time.localtime(t_df.index[-1]))
interval_df[time_str] = t_df.iloc[-1]-t_df.iloc[0]
start = end
return interval_df.T
# return t_df.iloc[-1]-t_df.iloc[0]
# return t_df
def av_title():
s = read_pickle('time_series.pkl')
title = list(s[s.index[-1]]['title'])
av_ls = list(s[s.index[-1]]['AV'])
print('av号与标题对照如下：')
for i in range(len(av_ls)):
print(str(av_ls[i]) + '\t' + str(title[i]))
def accumulate(kinds='all', start_time='default', end_time='default', av='all'):
# 处理默认kinds参数
if kinds == 'all':
kinds = ['view', 'like', 'coin', 'favourite', 'danmu', 'share', 'reply']
# 读取爬虫所保存的数据
s = read_pickle('time_series.pkl')
# 在series的时候对时间进行选取更为方便
s = select_time(s, start_time, end_time)
# 为fig做准备
sub_row, sub_col, fig = prep_plt(kinds)
# 循环画多个子图
for i in range(len(kinds)):
# 将series转换为dataframe
df = sort_by(s, kinds[i], av)
# 画子图
plt_line(df, kinds[i], fig, sub_row, sub_col, i+1)
fig.show()
def increase(kinds='all', start_time='default', end_time='default', av='all', interval=86400):
# 处理默认kinds参数
if kinds == 'all':
kinds = ['view', 'like', 'coin', 'favourite', 'danmu', 'share', 'reply']
# 读取爬虫所保存的数据
s = read_pickle('time_series.pkl')
# 在series的时候对时间进行选取更为方便
s = select_time(s, start_time, end_time)
# 为fig做准备
sub_row, sub_col, fig = prep_plt(kinds)
# 循环画多个kinds子图
for i in range(len(kinds)):
# 将series转换为dataframe
df = sort_by(s, kinds[i], av)
df_increase = get_interval(df, interval)
# 画子图
plt_bar(df_increase, kinds[i], fig, sub_row, sub_col, i+1)
fig.show()
# 画增长量柱状图
increase(kinds=['view'], av=[540421569, 840501089, 200633855], start_time='2020-6-10 12:00', interval=84600)
# # 画累计折线图
# accumulate(kinds=['view', 'coin'], av=[540421569, 840501089], start_time='2020-5-10 12:00')