[draw the competition diagram with a few lines of pandas_live] 3 Scatter diagram (test code + dataset + drawing parameter analysis)

Posted by JDBurnZ on Tue, 18 Jan 2022 05:57:24 +0100

Resource file download:
Column learning instructions (configured venv virtual environment + take and use test code + test data set + parameter api analysis)

Preview of all renderings:
Rendering display (configured venv virtual environment + take and use test code + test data set + parameter api analysis)

Environment configuration:
Environment configuration and detection (configured venv virtual environment + ready to use test code + test data set + parameter api analysis)

3. Scatter diagram

A reminder appears:

E:\allworkspace\python work space\Python Dynamic graph_pandas_alive\pandas_alive\charts.py:420: UserWarning: Discarding nonzero nanoseconds in conversion
  super().set_x_y_limits(self.df, i, self.ax)

User warning: converting super() set_ x_ y_ I understand that discarding non-zero nanoseconds in limits (self. DF, I, self. Ax) should be the loss of accuracy and will not affect the drawing.

Scatter diagram API Description:

parse_dates={"Timestamp": ["Year", "Month", "Day"]}

The parsed data is in year month day format

dt.strftime('%Y/%m/%d')

Standardize this column of data format to output year month day

kind='scatter',

kind = "scatter", the chart type is scatter chart

keep_columns = ["Minimum temperature (Degree C)", "Maximum temperature (Degree C)"]

Set legend content

Scatter chart dataset

Newcastle_Australia_Max_Temps.csv
Newcastle_Australia_Min_Temps.csv
The amount of data is too large, and the step-by-step code cloud downloads the data set

https://gitee.com/miao-zehao/pandas-live-game-graph

Scatter routine

# @Time    : 2022/1/12 19:57
# @Author: Nanli
# @FileName: 3..py

import pandas as pd

######Display Chinese Song typeface import. If you use Chinese, add this code######
import matplotlib as plt

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
#####################################################

import pandas as pd
import pandas_alive

max_temp_df = pd.read_csv(
    "data source data/Newcastle_Australia_Max_Temps.csv",
    parse_dates={"Timestamp": ["Year", "Month", "Day"]},
)
min_temp_df = pd.read_csv(
    "data source data/Newcastle_Australia_Min_Temps.csv",
    parse_dates={"Timestamp": ["Year", "Month", "Day"]},
)

merged_temp_df = pd.merge_asof(max_temp_df, min_temp_df, on="Timestamp")

merged_temp_df.index = pd.to_datetime(merged_temp_df["Timestamp"].dt.strftime('%Y/%m/%d'))

#Set legend content
keep_columns = ["Minimum temperature (Degree C)", "Maximum temperature (Degree C)"]

merged_temp_df[keep_columns].resample("Y").mean().plot_animated(
    filename='3.Scatter diagram.gif',
    kind="scatter",#The chart type is scatter chart
    title='Find you far away - 3.Scatter diagram'
)

summary

If you find that you are far away from the @mzh original work, you must mark the original link for reprint

Crated: 2022-1-13

I've been tossing around for a week and sorted out a lot of methods for getting started with Xiaobai lightning protection, which will continue to be updated. If it's helpful to you, I hope to get your praise 👍 Collection support! (after all, it's too difficult to finish learning in a short time. It's recommended to put it in your favorites to eat ash)

Topics: Python TensorFlow data visualization

Programmer Think