[Visualization] I want to draw a beautiful graph with Plotly
this is
Plotly can draw beautiful graphs with a small amount of code, but since I used only matplotlib and did not know much, it is a memorandum of the person who tried to get started while checking.
environment
Google colaboratory
Installation
If it is colab, there is no installation, but if you need it, you can install it with pip
pip install plotly
Data preparation
I have time series data that can be used immediately with seaborn, so I will use it. The following is data preparation, so skip it
import seaborn as sns
import pandas as pd
from calendar import month_name
month_name_mappings = {name[:3]: n for n, name in enumerate(month_name)}
#Just data preparation
df = sns.load_dataset('flights')
df["month"] = df.month.apply(lambda x: month_name_mappings[x])
df["year-month"] = pd.to_datetime(df.year.astype(str) + "-" + df.month.astype(str))
ts_data = df[["passengers", "year-month"]].set_index("year-month")["passengers"]
ts_data
year-month
1949-01-01 112
1949-02-01 118
1949-03-01 132
1949-04-01 129
1949-05-01 121
...
1960-08-01 606
1960-09-01 508
1960-10-01 461
1960-11-01 390
1960-12-01 432
Name: passengers, Length: 144, dtype: int64
Simple data on the number of passengers per month.
basic operation
I will create a graph
import plotly.graph_objects as go
fig = go.Figure()
fig.show()
Now you have a graph.
#Line graph
fig = go.Figure()
fig.add_trace(go.Scatter(x=ts_data.index, y=ts_data.values, name="passengers"))
fig.show()
Try to display the memory in logarithm
#Line graph
fig = go.Figure()
fig.add_trace(go.Scatter(x=ts_data.index, y=ts_data.values, name="passengers"))
#To customize the appearance, play with layout
fig.update_layout(yaxis_type="log")
fig.show()
I want to draw a gorgeous graph
I want to make it more luxurious, so I will try to visualize it in various ways.
--Split the data by month and make a line graph of the changes in each data --Try to make a bar graph of the total number of passengers for each year
#Knead the data a little
ts_data_monthly = df.groupby("month")["passengers"].apply(list)
ts_sum_yearly = df.groupby("year")["passengers"].sum()
#I want to make multiple line graphs
ts_data_monthly
month
1 [112, 115, 145, 171, 196, 204, 242, 284, 315, ...
2 [118, 126, 150, 180, 196, 188, 233, 277, 301, ...
3 [132, 141, 178, 193, 236, 235, 267, 317, 356, ...
4 [129, 135, 163, 181, 235, 227, 269, 313, 348, ...
5 [121, 125, 172, 183, 229, 234, 270, 318, 355, ...
6 [135, 149, 178, 218, 243, 264, 315, 374, 422, ...
7 [148, 170, 199, 230, 264, 302, 364, 413, 465, ...
8 [148, 170, 199, 242, 272, 293, 347, 405, 467, ...
9 [136, 158, 184, 209, 237, 259, 312, 355, 404, ...
10 [119, 133, 162, 191, 211, 229, 274, 306, 347, ...
11 [104, 114, 146, 172, 180, 203, 237, 271, 305, ...
12 [118, 140, 166, 194, 201, 229, 278, 306, 336, ...
Name: passengers, dtype: object
#I want to make a bar graph
ts_sum_yearly
year
1949 1520
1950 1676
1951 2042
1952 2364
1953 2700
1954 2867
1955 3408
1956 3939
1957 4421
1958 4572
1959 5140
1960 5714
Name: passengers, dtype: int64
#label(x axis)
ts_labels = ts_sum_yearly.index
ts_labels
Int64Index([1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959,
1960],
dtype='int64', name='year')
Let's visualize it. I played with the layout a little.
fig = go.Figure()
#Make a line graph for monthly time series data
for month, passengers in ts_data_monthly.iteritems():
fig.add_trace(go.Scatter(x=ts_labels, y=passengers, name=str(month)+"Month", yaxis='y2'))
#Make a bar graph for the yearly total
fig.add_trace(go.Bar(x=ts_labels, y=ts_sum_yearly.values, name="total", yaxis="y1"))
#To customize the appearance, play with layout
#Since there are two axes, there is no memory
fig.update_layout(
title={
"text": "Passenger number time series data",
"x":0.5,
"y": 0.9
},
legend={
"orientation":"h",
"x":0.5,
"xanchor":"center"
},
yaxis1={
"title": "Number of passengers(total)",
"side": "left",
"showgrid":False
},
yaxis2={
"title": "Number of passengers(By month)",
"side": "right",
"overlaying": "y",
"showgrid":False
}
)
fig.show()
You can flutter the legend. It's amazing to be able to draw a graph that can be moved a little with such a small amount of code ...
Other
Donuts (cute)
import numpy as np
ts_sum_monthly = df.groupby("month")["passengers"].sum()
#Make it look like a moon-cut pizza with the most passengers
pull=[0]*12
pull[np.argmax(ts_sum_monthly.values)] = 0.2
fig = go.Figure()
fig.add_trace(go.Pie(
labels=[str(month) + "Month" for month in ts_sum_monthly.index],
values=ts_sum_monthly.values,
hole=.3,
pull=pull
)
)
fig.update_layout(
title={
"text": "Percentage of passengers(1949~1960 total)",
"x":0.5,
"y": 0.9
}
)
fig.show()
Create a pie chart for the total number of passengers each year
from plotly.subplots import make_subplots
specs = [[{'type':'domain'}, {'type':'domain'}, {'type':'domain'}, {'type':'domain'}] for _ in range(3)]
# 3*Divide the graph into 4 grids
fig = make_subplots(rows=3, cols=4, specs=specs)
#The position of the label title in each pie chart of the label
pos_x = [0.09, 0.37, 0.63, 0.91]
pos_y = [0.9, 0.5, 0.1]
annotations = []
# (row, col)Place a pie chart at the position of
row = 0
for i, (year, df_yearly) in enumerate(df.groupby(["year"])[["month","passengers"]]):
pull=[0]*12
pull[np.argmax(df_yearly.passengers.values)] = 0.2
col = i%4+1
if col == 1:
row += 1
annotations.append({
"text": str(year)+"Year",
"x": pos_x[col-1],
"y": pos_y[row-1],
"font_size": 10,
"showarrow":False
})
fig.add_trace(go.Pie(
labels=[str(month) + "Month" for month in df_yearly.month.values],
values=df_yearly.passengers.values,
name=str(year)+"Year",
hole=.3,
pull=pull
),
row, col
)
fig.update_layout(
title={
"text": "Percentage of passengers(Yearly)",
"x":0.5,
"y": 0.9
},
annotations=annotations
)
fig.show()
the end
Am I the only one who is happy that the graphs work? Next time I would like to summarize a web framework called dash that allows you to create dashboards with plotly.