HOWTO · Pandas
Pandas コラム fillna
このチュートリアルでは、DataFrame.fillna()メソッドを使って、NaN の値を指定した値で埋める方法を説明します。
このチュートリアルでは、DataFrame.fillna() メソッドを使って、NaN の値を指定した値で埋める方法を説明します。
この記事では、以下の DataFrame を使用します。
import numpy as np
import pandas as pd
roll_no = [501, 502, 503, 504, 505]
student_df = pd.DataFrame(
{
"Roll No": [501, 502, np.nan, 504, 505, 506],
"Name": ["Jennifer", "Travis", "Bob", "Emma", "Luna", "Anish"],
"Income(in $)": [200, 400, np.nan, 30, np.nan, np.nan],
"Age": [17, 18, np.nan, 16, 18, np.nan],
}
)
print(student_df)
出力：
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 NaN Bob NaN NaN
3 504.0 Emma 30.0 16.0
4 505.0 Luna NaN 18.0
5 506.0 Anish NaN NaN
DataFrame.fillna() メソッド
構文
DataFrame.fillna(
value=None, method=None, axis=None, inplace=False, limit=None, downcast=None
)
DataFrame.fillna() メソッドを用いると、DataFrame の NaN の値を指定した value または method で埋めることができます。
DataFrame.fillna() メソッドを用いて指定した値で DataFrame 全体を埋める
import numpy as np
import pandas as pd
roll_no = [501, 502, 503, 504, 505]
student_df = pd.DataFrame(
{
"Roll No": [501, 502, np.nan, 504, 505, 506],
"Name": ["Jennifer", "Travis", "Bob", "Emma", "Luna", "Anish"],
"Income(in $)": [200, 400, np.nan, 30, np.nan, np.nan],
"Age": [17, 18, np.nan, 16, 18, np.nan],
}
)
filled_df = student_df.fillna(0)
print("DataFrame with NaN values")
print(student_df, "\n")
print("After applying fillna() to the DataFrame:")
print(filled_df, "\n")
出力：
DataFrame with NaN values
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 NaN Bob NaN NaN
3 504.0 Emma 30.0 16.0
4 505.0 Luna NaN 18.0
5 506.0 Anish NaN NaN
After applying fillna() to the DataFrame:
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 0.0 Bob 0.0 0.0
3 504.0 Emma 30.0 16.0
4 505.0 Luna 0.0 18.0
5 506.0 Anish 0.0 0.0
DataFrame student_df のすべての NaN 値を DataFrame.fillna() メソッドの引数として渡された 0 で置き換えます。
import numpy as np
import pandas as pd
roll_no = [501, 502, 503, 504, 505]
student_df = pd.DataFrame(
{
"Roll No": [501, 502, np.nan, 504, 505, 506],
"Name": ["Jennifer", "Travis", "Bob", "Emma", "Luna", "Anish"],
"Income(in $)": [200, 400, np.nan, 30, np.nan, np.nan],
"Age": [17, 18, np.nan, 16, 18, np.nan],
}
)
filled_df = student_df.fillna(method="ffill")
print("DataFrame with NaN values")
print(student_df, "\n")
print("After applying fillna() to the DataFrame:")
print(filled_df, "\n")
出力：
DataFrame with NaN values
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 NaN Bob NaN NaN
3 504.0 Emma 30.0 16.0
4 505.0 Luna NaN 18.0
5 506.0 Anish NaN NaN
After applying fillna() to the DataFrame:
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 502.0 Bob 400.0 18.0
3 504.0 Emma 30.0 16.0
4 505.0 Luna 30.0 18.0
5 506.0 Anish 30.0 18.0
student_df に含まれるすべての NaN 値を NaN 値と同じ列にある NaN 値の前の値で埋めます。
指定したカラムの NaN の値を指定した値で埋める
特定の値を指定した値で埋めるには、カラム名をキーに、そのカラムの NaN 値に使用する値を値として fillna() メソッドに辞書を渡します。
import numpy as np
import pandas as pd
roll_no = [501, 502, 503, 504, 505]
student_df = pd.DataFrame(
{
"Roll No": [501, 502, np.nan, 504, 505, 506],
"Name": ["Jennifer", "Travis", "Bob", "Emma", "Luna", "Anish"],
"Income(in $)": [200, 400, np.nan, 300, np.nan, np.nan],
"Age": [17, 18, np.nan, 16, 18, np.nan],
}
)
filled_df = student_df.fillna({"Age": 17, "Income(in $)": 300})
print("DataFrame with NaN values")
print(student_df, "\n")
print("After applying fillna() to the DataFrame:")
print(filled_df, "\n")
出力：
DataFrame with NaN values
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 NaN Bob NaN NaN
3 504.0 Emma 300.0 16.0
4 505.0 Luna NaN 18.0
5 506.0 Anish NaN NaN
After applying fillna() to the DataFrame:
Roll No Name Income(in $) Age
0 501.0 Jennifer 200.0 17.0
1 502.0 Travis 400.0 18.0
2 NaN Bob 300.0 17.0
3 504.0 Emma 300.0 16.0
4 505.0 Luna 300.0 18.0
5 506.0 Anish 300.0 17.0
このメソッドは Age カラムの NaN 値をすべて値 17 で埋め、Income(in $) カラムの NaN 値をすべて値 300 で埋めます。Roll No カラムの NaN 値はそのまま残されます。
