Pengantar ilmu data dalam solusi penugasan minggu 1 python

Untuk tugas ini, Anda akan melihat data tahun 2017 tentang imunisasi dari CDC. File data Anda untuk penugasan ini ada di assets/NISPUF17. csv. Panduan pengguna data untuk ini, yang Anda perlukan untuk memetakan variabel dalam data ke pertanyaan yang diajukan, tersedia di aset/NIS-PUF17-DUG. pdf. Catatan. Anda mungkin harus pergi ke pohon Jupyter Anda (klik pada gambar Coursera) dan arahkan ke folder aset tugas 2 untuk melihat file PDF ini)

pertanyaan 1

Write a function called

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Fungsi ini harus mengembalikan kamus dalam bentuk (gunakan angka yang benar, jangan membulatkan angka)

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{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

Kode

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def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

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assert type(proportion_of_education())==type({}), "You must return a dictionary."
assert len(proportion_of_education()) == 4, "You have not returned a dictionary with four items in it."
assert "less than high school" in proportion_of_education().keys(), "You have not returned a dictionary with the correct keys."
assert "high school" in proportion_of_education().keys(), "You have not returned a dictionary with the correct keys."
assert "more than high school but not college" in proportion_of_education().keys(), "You have not returned a dictionary with the correct keys."
assert "college" in proportion_of_education().keys(), "You have not returned a dictionary with the correct keys."

结果

Pertanyaan 2

Mari jelajahi hubungan antara diberi ASI saat masih kecil dan mendapatkan vaksin influenza musiman dari penyedia layanan kesehatan. Kembalikan sejumlah rata-rata jumlah vaksin influenza untuk anak-anak yang kami tahu menerima ASI saat masih kecil dan mereka yang tahu tidak

Fungsi ini harus mengembalikan tuple dalam bentuk (gunakan nomor yang benar

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(2.5, 0.1)

Kode

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def average_influenza_doses():
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    
    cbf_flu=df.loc[:,['CBF_01','P_NUMFLU']]
    
    
    cbf_flu1=cbf_flu[cbf_flu['CBF_01'] ==1].dropna()
    cbf_flu2=cbf_flu[cbf_flu['CBF_01'] ==2].dropna()
    
    flu1=cbf_flu1['P_NUMFLU'].values.copy()
    flu1[np.isnan(flu1)] = 0
    f1=np.sum(flu1)/len(flu1)
    
    flu2=cbf_flu2['P_NUMFLU'].values.copy()
    flu2[np.isnan(flu2)] = 0
    f2=np.sum(flu2)/len(flu2)
    
    aid =(f1,f2)
    return aid

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{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

结果

Fungsi ini harus mengembalikan kamus dalam bentuk (gunakan angka yang benar)

{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

Catatan. Untuk membantu verifikasi, nilai

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Kode

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{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

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{"less than high school":0.2,
"high school":0.4,
"more than high school but not college":0.2,
"college":0.2}

结果

Pertanyaan 4

Korelasi adalah hubungan statistik antara dua variabel. Jika kita ingin mengetahui apakah vaksin bekerja, kita dapat melihat korelasi antara penggunaan vaksin dan apakah itu menghasilkan pencegahan infeksi atau penyakit [1]. Dalam pertanyaan ini, Anda akan melihat apakah ada korelasi antara pernah terkena cacar air dan jumlah dosis vaksin cacar air yang diberikan (varicella)

Beberapa catatan tentang menafsirkan jawabannya.

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def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

Juga,

def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

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def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

def proportion_of_education():
    # your code goes here
    # YOUR CODE HERE
    # raise NotImplementedError()
    import pandas as pd
    import numpy as np
    df = pd.read_csv("assests/NISPUF17.csv", index_col=0)
    EDUS=df['EDUC1']
    edus=np.sort(EDUS.values)
    poe={"less than high school":0,
        "high school":0,
        "more than high school but not college":0,
        "college":0}
    n=len(edus)
    poe["less than high school"]=np.sum(edus==1)/n
    poe["high school"]=np.sum(edus==2)/n
    poe["more than high school but not college"]=np.sum(edus==3)/n
    poe["college"]=np.sum(edus==4)/n
    return poe

[1] Ini bukan gambaran lengkapnya, karena kita tidak melihat kapan dosis diberikan. Ada kemungkinan anak-anak menderita cacar air dan kemudian orang tua mereka pergi untuk mendapatkan vaksin. Apakah kumpulan data ini memiliki data yang kami perlukan untuk menyelidiki waktu pemberian dosis?

Bagaimana cara saya berlatih Python untuk Ilmu Data?

Apa topik dalam Python untuk Ilmu Data?

Bagaimana cara menguasai Python untuk media Ilmu Data?

Seberapa baik Python untuk Ilmu Data?