Python periksa apakah kerangka data ada

Bagaimana cara memeriksa apakah satu kolom atau beberapa kolom ada di pandas DataFrame? . Pada artikel ini, saya akan menjelaskan beberapa cara bagaimana memeriksa Jika ada kolom di pandas DataFrame dengan contoh

1. Contoh Cepat Periksa Jika Kolom Ada di Pandas DataFrame

Jika Anda terburu-buru, di bawah ini adalah beberapa contoh cepat tentang cara memeriksa apakah ada kolom di pandas DataFrame

# Below are quick example # Check if column Courses is in DataFrame.columns if 'Courses' in df.columns: print("Courses column is present : Yes") else: print("Courses column is present : No") # Check if column Courses is in DataFrame if 'Courses' in df: print("Courses column is present : Yes") else: print("Courses column is present : No") # Check if column Courses is not in DataFrame.columns if 'Courses' not in df.columns: print("Courses column is present : Yes") else: print("Courses column is present : No") # Check for multiple columns all exist Using set.issubset if set(['Courses','Duration']).issubset(df.columns): print("Courses column is present : Yes") else: print("Courses column is present : No") # By using curly braces to issubset DataFrame.coluns if {'Courses','Duration'}.issubset(df.columns): print("Courses column is present : Yes") else: print("Courses column is present : No") # To check if one or more columns all exist in DataFrame if all([item in df.columns for item in ['Fee','Discount']]): print("Courses column is present : Yes") else: print("Courses column is present : No") _

Sekarang, mari buat DataFrame dengan beberapa baris dan kolom, jalankan contoh ini dan validasi hasilnya. DataFrame kami berisi nama kolom import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) 4, import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) 5, import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) 6, dan import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) 7

import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df)

Hasil di bawah output

Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000

2. Periksa Jika Kolom Tunggal Ada di DataFrame

Gunakan kolom DataFrame dengan kondisi if untuk memeriksa apakah ada kolom. Mari kita lihat apakah kolom import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) _8 ada di pandas DataFrame. Bingkai Data. kolom mengembalikan daftar semua label kolom

# Check if column Courses is in DataFrame.columns if 'Courses' in df.columns: print("Courses column is present : Yes") else: print("Courses column is present : No") _

Hasil di bawah output

Courses column is present : Yes

Atau, Anda juga dapat menulisnya sebagai

# Check if column Courses is in DataFrame if 'Courses' in df: print("Courses column is present : Yes") else: print("Courses column is present : No")

3. Periksa Jika Kolom Tidak Ada di DataFrame

Untuk memeriksa apakah kolom import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) _9 ada di DataFrame atau tidak, gunakan not di operator. Misalnya, Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 _0 metode

# Check if column Courses is not in DataFrame.columns if 'XYZ' not in df.columns: print("XYZ column is present : NO") else: print("XYZ column is present : Yes")

Hasil di bawah output

XYZ column is present : NO

4. Periksa Beberapa Kolom Ada di Pandas DataFrame

Untuk memeriksa apakah ada daftar beberapa kolom yang dipilih di pandas DataFrame, gunakan Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 1. Misalnya, metode Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 _2

# Check for multiple columns all exist Using set.issubset if set(['Courses','Duration']).issubset(df.columns): print("Columns is present : Yes") else: print("Columns is present : No")

Hasil di bawah output

Columns is present : Yes

Untuk Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 _3 alternatif dapat dibangun dengan kurung kurawal

import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) 0

Menghasilkan output yang sama seperti di atas

5. Untuk Memeriksa Apakah Satu atau Lebih Kolom Semua Ada di DataFrame

Untuk memeriksa apakah satu atau lebih kolom ada di pandas DataFrame, gunakan pemahaman daftar, seperti pada. Misalnya, Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 _4

import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) _1

Menghasilkan output yang sama seperti di atas

6. Contoh Lengkap Untuk Memeriksa Jika Kolom Ada di DataFrame

import pandas as pd technologies = { 'Courses':["Spark","PySpark","Python","pandas"], 'Fee' :[20000,25000,22000,30000], 'Duration':['30days','40days','35days','50days'], 'Discount':[1000,2300,1200,2000] } index_labels=['r1','r2','r3','r4'] df = pd.DataFrame(technologies,index=index_labels) print(df) _2

Kesimpulan

Pada artikel ini, Anda telah mempelajari cara memeriksa Jika kolom ada di DataFrame dan jika kolom tidak ada dengan menggunakan metode daftar dan atur kondisi if. Anda bisa mendapatkan semua label kolom DataFrame dengan menggunakan Courses Fee Duration Discount r1 Spark 20000 30days 1000 r2 PySpark 25000 40days 2300 r3 Python 22000 35days 1200 r4 pandas 30000 50days 2000 5

Bagaimana cara saya memeriksa apakah DataFrame ada di Python?

Bagaimana Anda memeriksa apakah ada data di DataFrame?

Bagaimana Anda memeriksa apakah DataFrame ada atau tidak di PySpark?

Bagaimana Anda memeriksa apakah ada nilai dalam Pandas DataFrame dengan Python?