[Python] Pandas – Seriesに要素を追加する方法

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# 新しいSeriesを作成
new_series = pd.Series([4, 5])
# append()メソッドを使って要素を追加
result_series = original_series.append(new_series)
print(result_series)

0    1
1    2
2    3
0    4
1    5
dtype: int64

import pandas as pd
# 既存のSeries
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# concat()関数を使って要素を追加
result_series = pd.concat([series1, series2])
print(result_series)

0    1
1    2
2    3
0    4
1    5
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# loc[]を使って新しい要素を追加
original_series.loc[3] = 4
print(original_series)

0    1
1    2
2    3
3    4
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# at[]を使って新しい要素を追加
original_series.at[3] = 4
print(original_series)

0    1
1    2
2    3
3    4
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# iloc[]を使って新しい要素を追加
original_series.iloc[3] = 4
print(original_series)

0    1
1    2
2    3
3    4
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# 新しいSeriesを作成
new_series = pd.Series([4, 5])
# append()メソッドを使って要素を追加
result_series = original_series.append(new_series)
print(result_series)

0    1
1    2
2    3
0    4
1    5
dtype: int64

import pandas as pd
# 既存のSeries
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
series3 = pd.Series([6, 7])
# append()メソッドを使って複数のSeriesを結合
result_series = series1.append([series2, series3])
print(result_series)

0    1
1    2
2    3
0    4
1    5
0    6
1    7
dtype: int64

import pandas as pd
# 既存のSeries
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# ignore_indexオプションを使ってインデックスを再設定
result_series = series1.append(series2, ignore_index=True)
print(result_series)

0    1
1    2
2    3
3    4
4    5
dtype: int64

import pandas as pd
# 既存のSeries
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# concat()関数を使って要素を追加
result_series = pd.concat([series1, series2])
print(result_series)

0    1
1    2
2    3
0    4
1    5
dtype: int64

import pandas as pd
# 既存のSeries
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# concat()関数を使ってSeriesを結合
result_series = pd.concat([series1, series2])
print(result_series)

0    1
1    2
2    3
0    4
1    5
dtype: int64

import pandas as pd
# 複数のSeriesを作成
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
series3 = pd.Series([6, 7])
# concat()関数を使って複数のSeriesを結合
result_series = pd.concat([series1, series2, series3])
print(result_series)

0    1
1    2
2    3
0    4
1    5
0    6
1    7
dtype: int64

import pandas as pd
# 2つのDataFrameを作成
df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
# axis=0で行方向に結合
result_df_row = pd.concat([df1, df2], axis=0)
# axis=1で列方向に結合
result_df_col = pd.concat([df1, df2], axis=1)
print("行方向に結合:")
print(result_df_row)
print("\n列方向に結合:")
print(result_df_col)

行方向に結合:
   A  B
0  1  3
1  2  4
0  5  7
1  6  8
列方向に結合:
   A  B  A  B
0  1  3  5  7
1  2  4  6  8

import pandas as pd
# 複数のSeriesを作成
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# ignore_indexオプションを使ってインデックスを再設定
result_series = pd.concat([series1, series2], ignore_index=True)
print(result_series)

0    1
1    2
2    3
3    4
4    5
dtype: int64

import pandas as pd
# 複数のSeriesを作成
series1 = pd.Series([1, 2, 3])
series2 = pd.Series([4, 5])
# keysオプションを使って階層的なSeriesを作成
result_series = pd.concat([series1, series2], keys=['A', 'B'])
print(result_series)

A  0    1
   1    2
   2    3
B  0    4
   1    5
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# loc[]を使って新しい要素を追加
original_series.loc[3] = 4  # インデックス3に4を追加
print(original_series)

0    1
1    2
2    3
3    4
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# at[]を使って新しい要素を追加
original_series.at[4] = 5  # インデックス4に5を追加
print(original_series)

0    1
1    2
2    3
4    5
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# iloc[]を使って新しい要素を追加
original_series.iloc[3] = 4  # 位置3に4を追加
print(original_series)

0    1
1    2
2    3
3    4
dtype: int64

import pandas as pd
# 空のSeriesを作成
dynamic_series = pd.Series()
# 動的にデータを追加
for i in range(5):
    dynamic_series = dynamic_series.append(pd.Series([i]))
print(dynamic_series)

0    0
0    1
0    2
0    3
0    4
dtype: int64

import pandas as pd
# 既存のSeries
original_series = pd.Series([1, 2, 3, 4, 5])
# 条件に基づいて要素を追加
for i in range(len(original_series)):
    if original_series[i] % 2 == 0:  # 偶数の場合
        original_series.loc[i + 5] = original_series[i] * 2  # 新しいインデックスに追加
print(original_series)

0    1
1    2
2    3
3    4
4    5
5    4
6    8
dtype: int64

import pandas as pd
import numpy as np
# 既存のSeries
original_series = pd.Series([1, 2, 3])
# NumPy配列を作成
new_data = np.array([4, 5, 6])
# NumPy配列をSeriesに変換して追加
result_series = original_series.append(pd.Series(new_data))
print(result_series)

0    1
1    2
2    3
0    4
1    5
2    6
dtype: int64

import pandas as pd
# DataFrameを作成
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)
# DataFrameの特定の列をSeriesに変換して追加
original_series = pd.Series([7, 8])
result_series = original_series.append(df['B'])
print(result_series)

0    7
1    8
0    4
1    5
2    6
dtype: int64