Upload data.py

data.py

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+import pandas as pd
+import numpy as np
+from sklearn import preprocessing
+import streamlit as st
+import joblib
+
+
+def getDataSetOrigin():
+    dataSet = [
+        ["青绿", "蜷缩", "浊响", "清晰", "凹陷", "硬滑", 1],
+        ["乌黑", "蜷缩", "沉闷", "清晰", "凹陷", "硬滑", 1],
+        ["乌黑", "蜷缩", "浊响", "清晰", "凹陷", "硬滑", 1],
+        ["青绿", "蜷缩", "沉闷", "清晰", "凹陷", "硬滑", 1],
+        ["浅白", "蜷缩", "浊响", "清晰", "凹陷", "硬滑", 1],
+        ["青绿", "稍蜷", "浊响", "清晰", "稍凹", "软粘", 1],
+        ["乌黑", "稍蜷", "浊响", "稍糊", "稍凹", "软粘", 1],
+        ["乌黑", "稍蜷", "浊响", "清晰", "稍凹", "硬滑", 1],
+        ["乌黑", "稍蜷", "沉闷", "稍糊", "稍凹", "硬滑", 0],
+        ["青绿", "硬挺", "清脆", "清晰", "平坦", "软粘", 0],
+        ["浅白", "硬挺", "清脆", "模糊", "平坦", "硬滑", 0],
+        ["浅白", "蜷缩", "浊响", "模糊", "平坦", "软粘", 0],
+        ["青绿", "稍蜷", "浊响", "稍糊", "凹陷", "硬滑", 0],
+        ["浅白", "稍蜷", "沉闷", "稍糊", "凹陷", "硬滑", 0],
+        ["乌黑", "稍蜷", "浊响", "清晰", "稍凹", "软粘", 0],
+        ["浅白", "蜷缩", "浊响", "模糊", "平坦", "硬滑", 0],
+        ["青绿", "蜷缩", "沉闷", "稍糊", "稍凹", "硬滑", 0],
+    ]
+    features = [
+        "color",
+        "root",
+        "knocks",
+        "texture",
+        "navel",
+        "touch",
+        "label",
+    ]
+    dataSet = np.array(dataSet)
+    dfOrigin = pd.DataFrame(dataSet, columns=features)
+    return dfOrigin
+
+
+def dataPreprocessing():
+    df = getDataSetOrigin()
+    for feature in df.columns[0:6]:
+        le = preprocessing.LabelEncoder()
+        le = le.fit(df[feature])
+        df[feature] = le.transform(df[feature])
+        joblib.dump(le, "./models/" + feature + "_LabelEncoder.model")
+    df["label"] = df["label"].astype(int)
+
+    return df
+
+
+def inputData():
+    st.sidebar.subheader("请选择西瓜外观:sunglasses:")
+    color = st.sidebar.selectbox("色泽", ("青绿", "乌黑", "浅白"))
+    root = st.sidebar.selectbox("根蒂", ("蜷缩", "稍蜷", "硬挺"))
+    knocks = st.sidebar.selectbox("敲击", ("浊响", "沉闷", "清脆"))
+    texture = st.sidebar.selectbox("纹理", ("清晰", "稍糊", "模糊"))
+    navel = st.sidebar.selectbox("脐部", ("凹陷", "稍凹", "平坦"))
+    touch = st.sidebar.selectbox("触感", ("硬滑", "软粘"))
+    input = [[color, root, knocks, texture, navel, touch]]
+    features = ["color", "root", "knocks", "texture", "navel", "touch"]
+    np.array(input).reshape(1, 6)
+    df_input = pd.DataFrame(input, columns=features, index=None)
+
+    for feature in features[0:6]:
+        le = joblib.load("./models/" + feature + "_LabelEncoder.model")
+        df_input[feature] = le.transform(df_input[feature])
+
+    return df_input