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lhg99 commited on May 19, 2023

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-# **Gradio-Demo**
-## - **Gradio**
-[<img src="readme_files/gradio.svg" alt="gradio" width=300>](https://gradio.app)<br>
-Here's the gradio github link: https://github.com/gradio-app/gradio
-Gradio is open-source python library. It can make demo for machine learning model.
-### Gradio is useful for:
-- **Demoing** your machine learning models for clients/collaborators/users/students.
-- **Deploying** your models quickly with automatic shareable links and getting feedback on model performance.
-- **Debugging** your model interactively during development using built-in manipulation and interpretation tools.
-We can use various components for making demos.
-This project provides demo for people who want to use gradio library.
-## - **Demo Description**
-This demo shows 2022 year weather in table and graph by selecting the month, day, weather elements, and location.
-### **Input components**
-Month, day : dropbox<br>
-weather elements : checkboxGroup<br>
-location : radio<br>
-precipitation : checkbox
-Precipitation data has few valid data, so we made a separate component without drawing a graph.
-### **Output components**
-Weather table : dataframe<br>
-Weather graph : plots
-We used pandas and matplotlib python library when we make dataframe and plots.
-Humidity is represented by a bar graph and other weather elements are represented by a curved line graphs.
-### **Function**
-In demo, we made two functions which names are dataSearch and showOutput.
-- dataSearch()
-This function provides obtaining data about the month, day, weather element, and location entered by the user.
-The columns in the csv file are composed of location, date, time, percipitation, wind, humidity, air pressure, and temperature. We took  csv files from weather data opening portal.
-```python
-def dataSearch(month, day, weather_elements, location, precipitation):
-    if location=='Seoul':
-        df = pd.read_csv('Seoul.csv')
-    elif location=='Washington':
-        df = pd.read_csv('Washington.csv')
-    if precipitation:
-        weather_elements.append('precipitation')
-    if day in ['1','2','3','4','5','6','7','8','9']:
-        today = '2022-'+month +'-0'+day
-    else:
-        today = '2022-'+month+'-'+day
-    df1 = df[df.date == today]
-    columns = ['location', 'date', 'time'] + weather_elements
-    df2 = df1.loc[:, columns]
-    return df2
-```
-- showOutput()
-This function represents data obtained from dataSearch() by dataframe and graphs.
-It replaced month with numeric form and the maximum number of plots increased to 2 depending on the weather elements selected.
-```python
-def showOutput(month, day, weather_elements, location, precipitation):
-    if month=='January':
-        month = '01'
-    elif month=='February':
-        month = '02'
-    elif month=='March':
-        month = '03'
-    elif month=='April':
-        month = '04'
-    elif month=='May':
-        month = '05'
-    elif month=='June':
-        month = '06'
-    elif month=='July':
-        month = '07'
-    elif month=='August':
-        month = '08'
-    elif month=='September':
-        month = '09'
-    elif month=='October':
-        month = '10'
-    elif month=='November':
-        month = '11'
-    elif month=='December':
-        month = '12'
-    weatherTable = dataSearch(month, day, weather_elements, location, precipitation)
-    if precipitation:
-        weather_elements.remove('precipitation')
-    if day in ['1','2','3','4','5','6','7','8','9']:
-        xname = '2022-'+month +'-0'+day
-    else:
-        xname = '2022-'+month+'-'+day
-    y_value=[0]*len(weather_elements)
-    for i in range(len(weather_elements)):
-        y_value[i] = weatherTable[weather_elements[i]]
-    x_value = weatherTable['time']
-    if 'humidity' in weather_elements:
-        humidity_index = weather_elements.index('humidity')
-        if weather_elements[humidity_index] != weather_elements[-1]:
-            temp = weather_elements[humidity_index]
-            weather_elements[humidity_index] = weather_elements[-1]
-            weather_elements[-1] = temp
-        if len(weather_elements) == 1:
-            weatherPlot = plt.figure(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xlabel(xname,labelpad=5, fontsize=15)
-            plt.ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            plt.xticks(size=10, rotation=45)
-            plt.bar(x_value, y_value[-1], color='skyblue', label='1st data')
-            plt.legend(loc = "upper left")
-        elif len(weather_elements) == 2:
-            weatherPlot, ax1 = plt.subplots(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xticks(size=10, rotation=45)
-            ax1.bar(x_value, y_value[-1], color='skyblue', label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[1], labelpad=15, fontsize=15)
-            ax1.legend(loc='upper left')
-            ax1_sub = ax1.twinx()
-            ax1_sub.plot(x_value, y_value[0], color='red', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[0], labelpad=25, fontsize=15, rotation=270)
-            ax1_sub.legend(loc='upper right')
-        elif len(weather_elements) == 3:
-            weatherPlot, (ax1, ax2) = plt.subplots(2, 1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='blue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.bar(x_value, y_value[-1], color='skyblue', label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[-1], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper right')
-        elif len(weather_elements) == 4:
-            weatherPlot, (ax1, ax2) = plt.subplots(2,1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='blue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.bar(x_value, y_value[-1], color='skyblue', label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[-1], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper left')
-            ax2_sub = ax2.twinx()
-            ax2_sub.plot(x_value, y_value[2], color='gray', marker = "o", label='4th data')
-            ax2_sub.set_ylabel(weather_elements[2], labelpad=25, fontsize=15, rotation=270)
-            ax2_sub.legend(loc='upper right')
-    else:
-        if len(weather_elements) == 1:
-            weatherPlot = plt.figure(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xlabel(xname,labelpad=5, fontsize=15)
-            plt.ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            plt.xticks(size=10, rotation=45)
-            plt.plot(x_value, y_value[0], color='red', marker='o', label='1st data')
-            plt.legend(loc = "upper left")
-        elif len(weather_elements) == 2:
-            weatherPlot, ax1 = plt.subplots(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xticks(size=10, rotation=45)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker='o', label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='skyblue', marker='o', label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-        elif len(weather_elements) == 3:
-            weatherPlot, (ax1, ax2) = plt.subplots(2,1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='skyblue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.plot(x_value, y_value[2], color='gray', marker = "o", label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[2], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper left')
-    return [weatherTable, weatherPlot]
-```
-## - Demo Usage
-Before you implement demo, you have to install gradio, pandas, and matplotlib library.
-```bash
-pip install gradio pandas matplotlib
-```
-Run the code below as a Python script or in a Jupyter Notebook or google colab.
-We provided demo code as a .ipynb file.
-```python
-import gradio as gr
-import pandas as pd
-import matplotlib.pyplot as plt
-# search weather data that is in csv file
-def dataSearch(month, day, weather_elements, location, precipitation):
-    if location=='Seoul':
-        df = pd.read_csv('Seoul.csv')
-    elif location=='Washington':
-        df = pd.read_csv('Washington.csv')
-    if precipitation:
-        weather_elements.append('precipitation')
-    if day in ['1','2','3','4','5','6','7','8','9']:
-        today = '2022-'+month +'-0'+day
-    else:
-        today = '2022-'+month+'-'+day
-    df1 = df[df.date == today]
-    columns = ['location', 'date', 'time'] + weather_elements
-    df2 = df1.loc[:, columns]
-    return df2
-# show weather data in plot using matplotlib
-def showOutput(month, day, weather_elements, location, precipitation):
-    if month=='January':
-        month = '01'
-    elif month=='February':
-        month = '02'
-    elif month=='March':
-        month = '03'
-    elif month=='April':
-        month = '04'
-    elif month=='May':
-        month = '05'
-    elif month=='June':
-        month = '06'
-    elif month=='July':
-        month = '07'
-    elif month=='August':
-        month = '08'
-    elif month=='September':
-        month = '09'
-    elif month=='October':
-        month = '10'
-    elif month=='November':
-        month = '11'
-    elif month=='December':
-        month = '12'
-    weatherTable = dataSearch(month, day, weather_elements, location, precipitation)
-    if precipitation:
-        weather_elements.remove('precipitation')
-    if day in ['1','2','3','4','5','6','7','8','9']:
-        xname = '2022-'+month +'-0'+day
-    else:
-        xname = '2022-'+month+'-'+day
-    y_value=[0]*len(weather_elements)
-    for i in range(len(weather_elements)):
-        y_value[i] = weatherTable[weather_elements[i]]
-    x_value = weatherTable['time']
-    if 'humidity' in weather_elements:
-        humidity_index = weather_elements.index('humidity')
-        if weather_elements[humidity_index] != weather_elements[-1]:
-            temp = weather_elements[humidity_index]
-            weather_elements[humidity_index] = weather_elements[-1]
-            weather_elements[-1] = temp
-        if len(weather_elements) == 1:
-            weatherPlot = plt.figure(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xlabel(xname,labelpad=5, fontsize=15)
-            plt.ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            plt.xticks(size=10, rotation=45)
-            plt.bar(x_value, y_value[-1], color='skyblue', label='1st data')
-            plt.legend(loc = "upper left")
-        elif len(weather_elements) == 2:
-            weatherPlot, ax1 = plt.subplots(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xticks(size=10, rotation=45)
-            ax1.bar(x_value, y_value[-1], color='skyblue', label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[1], labelpad=15, fontsize=15)
-            ax1.legend(loc='upper left')
-            ax1_sub = ax1.twinx()
-            ax1_sub.plot(x_value, y_value[0], color='red', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[0], labelpad=25, fontsize=15, rotation=270)
-            ax1_sub.legend(loc='upper right')
-        elif len(weather_elements) == 3:
-            weatherPlot, (ax1, ax2) = plt.subplots(2, 1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='blue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.bar(x_value, y_value[-1], color='skyblue', label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[-1], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper right')
-        elif len(weather_elements) == 4:
-            weatherPlot, (ax1, ax2) = plt.subplots(2,1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='blue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.bar(x_value, y_value[-1], color='skyblue', label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[-1], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper left')
-            ax2_sub = ax2.twinx()
-            ax2_sub.plot(x_value, y_value[2], color='gray', marker = "o", label='4th data')
-            ax2_sub.set_ylabel(weather_elements[2], labelpad=25, fontsize=15, rotation=270)
-            ax2_sub.legend(loc='upper right')
-    else:
-        if len(weather_elements) == 1:
-            weatherPlot = plt.figure(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xlabel(xname,labelpad=5, fontsize=15)
-            plt.ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            plt.xticks(size=10, rotation=45)
-            plt.plot(x_value, y_value[0], color='red', marker='o', label='1st data')
-            plt.legend(loc = "upper left")
-        elif len(weather_elements) == 2:
-            weatherPlot, ax1 = plt.subplots(figsize=(10,10))
-            plt.title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            plt.xticks(size=10, rotation=45)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker='o', label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='skyblue', marker='o', label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-        elif len(weather_elements) == 3:
-            weatherPlot, (ax1, ax2) = plt.subplots(2,1, figsize=(10,15), constrained_layout=True)
-            line1 = ax1.plot(x_value, y_value[0], color='red', marker = "o", label='1st data')
-            ax1.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax1.set_ylabel(weather_elements[0], labelpad=15, fontsize=15)
-            ax1.set_title("2022 Weather Graph", fontsize=20, fontweight='bold')
-            ax1.tick_params(axis='x', rotation=45, labelsize=10)
-            ax1_sub = ax1.twinx()
-            line2 = ax1_sub.plot(x_value, y_value[1], color='skyblue', marker = "o", label='2nd data')
-            ax1_sub.set_ylabel(weather_elements[1], labelpad=25, fontsize=15, rotation=270)
-            lines = line1 + line2
-            labels = [l.get_label() for l in lines]
-            ax1.legend(lines, labels, loc='upper left')
-            ax2.plot(x_value, y_value[2], color='gray', marker = "o", label='3rd data')
-            ax2.set_xlabel(xname, labelpad=5, fontsize=15)
-            ax2.set_ylabel(weather_elements[2], labelpad=15, fontsize=15)
-            ax2.tick_params(axis='x', rotation=45, labelsize=10)
-            ax2.legend(loc='upper left')
-    return [weatherTable, weatherPlot]
-output1 = gr.Dataframe()
-output2 = gr.Plot()
-# make gradio interface
-demo = gr.Interface(
-    fn=showOutput,
-    inputs=[
-        gr.Dropdown(["January", "February", "March", "April", "May","June",
-                     "July", "August", "September", "October", "November", "December"],label="Month", info="Select Months"),
-        gr.Dropdown(["1", "2", "3", "4", "5", "6", "7", "8", "9", "10",
-                     "11", "12", "13", "14", "15", "16", "17", "18", "19", "20",
-                     "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31"], label="Day", info="Select Day"),
-        gr.CheckboxGroup(["temperature(˚C)", "wind(m/s)", "humidity(%)", "air_pressure(hPa)"],
-                        label="Weather element", info="Choose weather element"),
-        gr.Radio(["Washington", "Seoul"], label="Location", info="Choose location"),
-        gr.Checkbox(label="precipation?")],
-        outputs=[output1,output2]
-)
-if __name__=="__main__":
-    demo.launch()
-```
-The demo below will appear automatically within the Jupyter Notebook, or pop in a browser on http://localhost:7860 if running from a script:
-![weather data demo](readme_files/screenshot.gif)

+---
+title: Gradio Demo
+emoji: 🐠
+colorFrom: indigo
+colorTo: gray
+sdk: gradio
+sdk_version: 3.29.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference