Python-科学计算-pandas-17-对某些列或行运算

import pandas as pd
import numpy as np
<p>dict_1 = {"value1": [10, 20, 30, 40, 50, 60, 70, 80],
"value2": [100, 200, 300, 400, 500, 600, 700, 800],
"value3": [50, 20, 30, 90, 50, 60, 80, 80],
"value4": [10, 30, 90, 40, 60, 60, 70, 80]}</p><p>df_1 = pd.DataFrame(dict_1, columns=["value1", "value2", "value3", "value4"])
print("\n", "df_1", "\n", df_1, "\n")
print(type(df_1))</p><h1>对某些列进行计算</h1><p>df_2 = df_1.apply(lambda x: np.square(x) if x.name in ['value1', 'value2'] else x)
print("\n", "df_2-列平方", "\n", df_2, "\n")</p><p>df_2 = df_1.apply(lambda x: x+2 if x.name in ['value1', 'value2'] else x)
print("\n", "df_2-列+2", "\n", df_2, "\n")</p><h1>对某些行进行计算</h1><p>df_3 = df_1.apply(lambda x: np.square(x) if x.name in [1, 2] else x, axis=1)
print("\n", "df_3-行平方", "\n", df_3, "\n")</p><p>df_3 = df_1.apply(lambda x: x-3 if x.name in [1, 2] else x, axis=1)
print("\n", "df_3-行-3", "\n", df_3, "\n")

axis

axis=0

axis=1

df_2 = df_1.apply(lambda x: np.square(x) if x.name in ['value1', 'value2'] else x)

apply

lambda

['value1', 'value2']

apply