Dash Plotly 如何修复 "All arguments should have the same length. x and y"
Dash Plotly how to fix "All arguments should have the same length. x and y"
我正在使用 Dash Plotly 制作图表。
当x和y长度相等时，Dash会显示图表，但当x和y长度不相等时，会报错。
这里是错误：
ValueError: All arguments should have the same length. The length of argument `y` is 3, whereas the length of previously-processed arguments ['x'] is 368
x 值:
DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04',
'2017-01-05', '2017-01-06', '2017-01-07', '2017-01-08',
'2017-01-09', '2017-01-10',
...
'2017-12-25', '2017-12-26', '2017-12-27', '2017-12-28',
'2017-12-29', '2017-12-30', '2017-12-31', '2018-01-01',
'2018-01-02', '2018-01-03'],
dtype='datetime64[ns]', length=368, freq='D')
Y值：
0 Violent protests
1 Confrontational protests (illegal and non viol...
7 Demonstrative protests (legal and nonviolent)
和图表：
graph = px.line(df, x=Date, y=Categories, color=Categories, markers=True,)
我要制作这张图表：
如何解决问题并制作此图表？
更新 1
整体数据：
图表的生成逻辑：
这张图片显示了上面的图表是如何使用 excel 生成的。
我想使用 Dash Plotly 生成相同的图表。
更新 2
CSV 文件中的所有数据：
id date_x Agency Relevance_x Human_Validation Event Categories of event start date end date Duration Issue Local-National Location_Category Location_Province Oganizer_type CivilSocietySector MainPoliticalSector CS_Location_Category CS_Location_Province size_of_participants Arena_type Arena_Province
45803 1/1/2018 7:19 ILNA Yes 1 Protest Violent protests 12/29/2017 12/29/2017 1 Economic National Town Khuzestan Unknown None Neutral National NONE unknown Streets Khuzestan
45817 1/1/2018 7:46 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Labour Local City Azerbaijan, East Workers Labour Neutral Province Center Azerbaijan, East medium group <50 Working places Azerbaijan, East
45531 1/1/2018 18:17 ILNA Yes 1 Protest Violent protests 1 Economic National City Isfahan Unknown None Neutral National NONE unknown Streets Isfahan
45529 1/1/2018 18:23 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Markazi Unknown None Neutral National NONE unknown Streets Markazi
45448 1/2/2018 6:36 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Kurdistan Unknown None Neutral National NONE unknown Streets Kurdistan
45299 1/2/2018 10:05 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Economic National Capital Tehran Unknown Student Movement Neutral Capital Tehran unknown University campuses Tehran
45029 1/3/2018 6:43 ILNA Yes 1 Protest Violent protests 1 Economic National Town Kermanshah Unknown None Neutral National NONE unknown Streets Kermanshah
44950 1/3/2018 8:49 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Bushehr GONGO Progovernment Conservative National Bushehr unknown Streets Bushehr
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/5/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
- 始终以文本而非图像形式提供示例数据
- 这很容易绘制，基于结构化数据。将 date 保留在索引中，每一列都是一行，它简化为
px.line(dfp, markers=True)
- 您问题的核心是您传递的数组不一致。使用结构化数据框
import pandas as pd
import numpy as np
import plotly.express as px
# fmt: off
L=24*5
events=["Protest"]
cat = ["Violent protests","Confrontational protests (illegal and non violent)","Demonstrative protests (legal and nonviolent"]
iss = ["Economic","Political","Labour"]
ln = ["Local","National"]
# generate some sample data...
df = pd.DataFrame({"date_x":pd.date_range("1-jan-2018", freq="1H", periods=L), "Event":np.random.choice(events,L),
"Categories of event":np.random.choice(cat, L), "Issue":np.random.choice(iss,L), "Local-National":np.random.choice(ln, L)})
# fmt: on
df = df.sample(50) # take random subset of data so total events varies by day
# sumarise data frame for plotting. NB dates are in the index
dfp = (
df.groupby([df["date_x"].dt.date, "Categories of event"])
.size()
.unstack("Categories of event")
.assign(Events=lambda d: d.sum(axis=1))
).fillna(0)
# now it's very simple to plot...
px.line(dfp, markers=True).update_layout(
xaxis={"dtick":"D"},
legend=dict(
yanchor="bottom", y=-1, xanchor="center", title_text="", x=.5
),
)
已更新 - 使用提供的样本数据
- 确保 date_x 是正确的数据类型
- 驱动总数的列是 事件
import io
import pandas as pd
import plotly.express as px
# fmt: off
df = pd.read_csv(io.StringIO("""id date_x Agency Relevance_x Human_Validation Event Categories of event start date end date Duration Issue Local-National Location_Category Location_Province Oganizer_type CivilSocietySector MainPoliticalSector CS_Location_Category CS_Location_Province size_of_participants Arena_type Arena_Province
45803 1/1/2018 7:19 ILNA Yes 1 Protest Violent protests 12/29/2017 12/29/2017 1 Economic National Town Khuzestan Unknown None Neutral National NONE unknown Streets Khuzestan
45817 1/1/2018 7:46 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Labour Local City Azerbaijan, East Workers Labour Neutral Province Center Azerbaijan, East medium group <50 Working places Azerbaijan, East
45531 1/1/2018 18:17 ILNA Yes 1 Protest Violent protests 1 Economic National City Isfahan Unknown None Neutral National NONE unknown Streets Isfahan
45529 1/1/2018 18:23 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Markazi Unknown None Neutral National NONE unknown Streets Markazi
45448 1/2/2018 6:36 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Kurdistan Unknown None Neutral National NONE unknown Streets Kurdistan
45299 1/2/2018 10:05 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Economic National Capital Tehran Unknown Student Movement Neutral Capital Tehran unknown University campuses Tehran
45029 1/3/2018 6:43 ILNA Yes 1 Protest Violent protests 1 Economic National Town Kermanshah Unknown None Neutral National NONE unknown Streets Kermanshah
44950 1/3/2018 8:49 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Bushehr GONGO Progovernment Conservative National Bushehr unknown Streets Bushehr
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/5/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan"""),
sep="\s\s+", engine="python")
# fmt: on
df["date_x"] = pd.to_datetime(df["date_x"])
dfp = (
df.groupby([df["date_x"].dt.date, "Event"])
.size()
.unstack("Event")
.assign(Events=lambda d: d.sum(axis=1))
).fillna(0)
# now it's very simple to plot...
px.line(dfp, markers=True).update_layout(
xaxis={"dtick":"D"},
legend=dict(
yanchor="bottom", y=-1, xanchor="center", title_text="", x=.5
),
)
我正在使用 Dash Plotly 制作图表。 当x和y长度相等时，Dash会显示图表，但当x和y长度不相等时，会报错。
这里是错误：
ValueError: All arguments should have the same length. The length of argument `y` is 3, whereas the length of previously-processed arguments ['x'] is 368
x 值:
DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04',
'2017-01-05', '2017-01-06', '2017-01-07', '2017-01-08',
'2017-01-09', '2017-01-10',
...
'2017-12-25', '2017-12-26', '2017-12-27', '2017-12-28',
'2017-12-29', '2017-12-30', '2017-12-31', '2018-01-01',
'2018-01-02', '2018-01-03'],
dtype='datetime64[ns]', length=368, freq='D')
Y值：
0 Violent protests
1 Confrontational protests (illegal and non viol...
7 Demonstrative protests (legal and nonviolent)
和图表：
graph = px.line(df, x=Date, y=Categories, color=Categories, markers=True,)
我要制作这张图表：
如何解决问题并制作此图表？
更新 1
整体数据：
图表的生成逻辑：
这张图片显示了上面的图表是如何使用 excel 生成的。
我想使用 Dash Plotly 生成相同的图表。
更新 2
CSV 文件中的所有数据：
id date_x Agency Relevance_x Human_Validation Event Categories of event start date end date Duration Issue Local-National Location_Category Location_Province Oganizer_type CivilSocietySector MainPoliticalSector CS_Location_Category CS_Location_Province size_of_participants Arena_type Arena_Province
45803 1/1/2018 7:19 ILNA Yes 1 Protest Violent protests 12/29/2017 12/29/2017 1 Economic National Town Khuzestan Unknown None Neutral National NONE unknown Streets Khuzestan
45817 1/1/2018 7:46 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Labour Local City Azerbaijan, East Workers Labour Neutral Province Center Azerbaijan, East medium group <50 Working places Azerbaijan, East
45531 1/1/2018 18:17 ILNA Yes 1 Protest Violent protests 1 Economic National City Isfahan Unknown None Neutral National NONE unknown Streets Isfahan
45529 1/1/2018 18:23 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Markazi Unknown None Neutral National NONE unknown Streets Markazi
45448 1/2/2018 6:36 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Kurdistan Unknown None Neutral National NONE unknown Streets Kurdistan
45299 1/2/2018 10:05 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Economic National Capital Tehran Unknown Student Movement Neutral Capital Tehran unknown University campuses Tehran
45029 1/3/2018 6:43 ILNA Yes 1 Protest Violent protests 1 Economic National Town Kermanshah Unknown None Neutral National NONE unknown Streets Kermanshah
44950 1/3/2018 8:49 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Bushehr GONGO Progovernment Conservative National Bushehr unknown Streets Bushehr
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/5/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
- 始终以文本而非图像形式提供示例数据
- 这很容易绘制，基于结构化数据。将 date 保留在索引中，每一列都是一行，它简化为
px.line(dfp, markers=True) - 您问题的核心是您传递的数组不一致。使用结构化数据框
import pandas as pd
import numpy as np
import plotly.express as px
# fmt: off
L=24*5
events=["Protest"]
cat = ["Violent protests","Confrontational protests (illegal and non violent)","Demonstrative protests (legal and nonviolent"]
iss = ["Economic","Political","Labour"]
ln = ["Local","National"]
# generate some sample data...
df = pd.DataFrame({"date_x":pd.date_range("1-jan-2018", freq="1H", periods=L), "Event":np.random.choice(events,L),
"Categories of event":np.random.choice(cat, L), "Issue":np.random.choice(iss,L), "Local-National":np.random.choice(ln, L)})
# fmt: on
df = df.sample(50) # take random subset of data so total events varies by day
# sumarise data frame for plotting. NB dates are in the index
dfp = (
df.groupby([df["date_x"].dt.date, "Categories of event"])
.size()
.unstack("Categories of event")
.assign(Events=lambda d: d.sum(axis=1))
).fillna(0)
# now it's very simple to plot...
px.line(dfp, markers=True).update_layout(
xaxis={"dtick":"D"},
legend=dict(
yanchor="bottom", y=-1, xanchor="center", title_text="", x=.5
),
)
已更新 - 使用提供的样本数据
- 确保 date_x 是正确的数据类型
- 驱动总数的列是 事件
import io
import pandas as pd
import plotly.express as px
# fmt: off
df = pd.read_csv(io.StringIO("""id date_x Agency Relevance_x Human_Validation Event Categories of event start date end date Duration Issue Local-National Location_Category Location_Province Oganizer_type CivilSocietySector MainPoliticalSector CS_Location_Category CS_Location_Province size_of_participants Arena_type Arena_Province
45803 1/1/2018 7:19 ILNA Yes 1 Protest Violent protests 12/29/2017 12/29/2017 1 Economic National Town Khuzestan Unknown None Neutral National NONE unknown Streets Khuzestan
45817 1/1/2018 7:46 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Labour Local City Azerbaijan, East Workers Labour Neutral Province Center Azerbaijan, East medium group <50 Working places Azerbaijan, East
45531 1/1/2018 18:17 ILNA Yes 1 Protest Violent protests 1 Economic National City Isfahan Unknown None Neutral National NONE unknown Streets Isfahan
45529 1/1/2018 18:23 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Markazi Unknown None Neutral National NONE unknown Streets Markazi
45448 1/2/2018 6:36 ILNA Yes 1 Protest Violent protests 1 Economic National Province Center Kurdistan Unknown None Neutral National NONE unknown Streets Kurdistan
45299 1/2/2018 10:05 ILNA Yes 1 Protest Confrontational protests (illegal and non violent) 1 Economic National Capital Tehran Unknown Student Movement Neutral Capital Tehran unknown University campuses Tehran
45029 1/3/2018 6:43 ILNA Yes 1 Protest Violent protests 1 Economic National Town Kermanshah Unknown None Neutral National NONE unknown Streets Kermanshah
44950 1/3/2018 8:49 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Bushehr GONGO Progovernment Conservative National Bushehr unknown Streets Bushehr
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National Province Center Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/3/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan
44935 1/5/2018 9:22 ILNA Yes 1 Protest Demonstrative protests (legal and nonviolent) 1 Political National City Khuzestan GONGO Progovernment Conservative National Khuzestan unknown Streets Khuzestan"""),
sep="\s\s+", engine="python")
# fmt: on
df["date_x"] = pd.to_datetime(df["date_x"])
dfp = (
df.groupby([df["date_x"].dt.date, "Event"])
.size()
.unstack("Event")
.assign(Events=lambda d: d.sum(axis=1))
).fillna(0)
# now it's very simple to plot...
px.line(dfp, markers=True).update_layout(
xaxis={"dtick":"D"},
legend=dict(
yanchor="bottom", y=-1, xanchor="center", title_text="", x=.5
),
)