Question

我正致力于为英雄联盟创造一些关于玩家游戏的分析。我尝试使用plotly创建直方图，日期范围在x轴上，没有。你的游戏。这有效，但我不能每个月都能获得单独的酒吧。我尝试过使用xaxis，＆＃39; size＆＃39;对象，但这不会改变任何东西，我猜因为x轴是日期形式。

所以问题，在Plotly中，如何将直方图上条形的大小从每月的bin大小更改为每日bin大小？

以下是代码示例：

from datetime import date, timedelta
import random
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
from plotly import tools
from plotly.offline import *#plotly.offline.iplot()
init_notebook_mode(connected=True)
############## create date ranges #################

d1 = date(2014, 3, 22)  # start date
d2 = date(2014, 6, 22)  # end date

delta = d2 - d1         # timedelta
dates = []
for i in range(delta.days + 1):
    dates.append((d1 + timedelta(days=i)))


#################################################


def games_p_day():
    sizeo = 1
    trace_total = go.Histogram(
        y=[random.randint(1, 10) for y in range(1, 100)],
        x=dates,
        name = 'total games',
        xbins=dict(
        size=sizeo
    )
        )
    trace_wins = go.Histogram(
        y=[random.randint(1, 10) for y in range(1, 100)],
        x=dates,
        name = 'won games',
        xbins=dict(
            size=sizeo
    )
        )
    trace_losses = go.Histogram(
        y=[random.randint(1, 10) for y in range(1, 100)],
        x=dates,
        name = 'lost games',
        xbins=dict(
        size=sizeo
    )
        )
    layout = dict(
        title = "Wins and losses over time",
        xaxis=dict(
            rangeselector=dict(
                buttons=list([
                    dict(count=1,
                         label='1m',
                         step='month',
                         stepmode='backward'),
                    dict(count=6,
                         label='6m',
                         step='month',
                         stepmode='backward'),
                    dict(step='all')
                ])
            ),
            rangeslider=dict(),
            type='date',

        ),
        bargap=0.2,
        bargroupgap=0.1)
    data=[trace_total]
    fig = go.Figure(data=data, layout=layout)
    iplot(fig, filename = "Wins and losses over time")    

games_p_day()

任何帮助都非常感激。哦，如果你看到其他任何可以帮助我的东西（即糟糕的代码结构），请告诉我！

Answer 1

直方图是数字数据的representation of the distribution。在我看来，您打算在此发布的是每天到每周的数据汇总。也就是说，只要您希望有一个时间维度，而不希望在x轴上进行计数，平均值或任何其他聚合函数。如果是这种情况，那么您面临挑战的关键就不在于图本身，而在于诸如resample('W-Mon', on='index').sum()之类的聚合和时间函数。以下是一些示例：

采样的原始数据图：

原始数据代码：

import pandas as pd
import numpy as np
import datetime

# data
np.random.seed(12)
numdays=100
dates = pd.date_range('1/1/2020', periods=numdays)
games = np.random.randint(low=100, high=200, size=numdays).tolist()
losses = np.random.randint(low=0, high=100, size=numdays).tolist()
wins = list(np.array(games)-np.array(wins))
df = pd.DataFrame({'games': games,
                        'wins':wins,
                        'losses':losses}, index=dates)

# resample daily data to weekly sums
df2=df.reset_index().resample('W-Mon', on='index').sum()
df2['formatted_date'] = pd.to_datetime(df3.index)
df2['year'] = df2.formatted_date.apply(lambda x: x.year)
df2['week_of_year'] = df2.formatted_date.apply(lambda x: x.weekofyear)
df2['year_week'] = df2['year'].map(str)+'_'+df3['week_of_year'].map(str)

# build and show plotly plot for daily games
fig = go.Figure(data=[go.Bar(name='games', x=df.index, y=df['games'])])
fig.show()

绘制每周汇总的数据。日期作为索引：

每周汇总数据的代码。日期作为索引：

# build and show plotly plot for weekly games. Dates as index
fig = go.Figure(data=[go.Bar(name='games', x=df2.index, y=df2['games'])])
fig.show()

绘制每周汇总的数据。年和周编号作为索引：

每周汇总数据的代码。年和周编号作为索引：

# build and show plotly plot for weekly games. Year and week number as index
fig = go.Figure(data=[go.Bar(name='games', x=df2['year_week'], y=df2['games'])])
fig.show()

绘制每周汇总数据的图表，按获胜和亏损进行划分：

每周汇总数据的代码，按获胜和失败分配：

import pandas as pd
import numpy as np
import datetime

# data
np.random.seed(12)
numdays=100
dates = pd.date_range('1/1/2020', periods=numdays)
games = np.random.randint(low=100, high=200, size=numdays).tolist()
losses = np.random.randint(low=0, high=100, size=numdays).tolist()
wins = list(np.array(games)-np.array(wins))
df = pd.DataFrame({'games': games,
                        'wins':wins,
                        'losses':losses}, index=dates)

# resample daily data to weekly sums
df2=df.reset_index().resample('W-Mon', on='index').sum()
df2['formatted_date'] = pd.to_datetime(df3.index)
df2['year'] = df2.formatted_date.apply(lambda x: x.year)
df2['week_of_year'] = df2.formatted_date.apply(lambda x: x.weekofyear)
df2['year_week'] = df2['year'].map(str)+'_'+df3['week_of_year'].map(str)

fig = go.Figure(data=[go.Bar(name='victory', x=df2['year_week'], y=df2['wins']),
                      go.Bar(name='defeat', x=df2['year_week'], y=df2['losses'])])



fig.update_layout(barmode='group')
fig.show()

如何改变条形图的时间序列

1 个答案: