准备工作（导入库、导入数据）
检测数据情况
DataFrame.drop(labels=None,axis=0, index=None, columns=None, inplace=False)
方式一：删除指定行或列
方式二：利用boolean删除满足条件元素所在的行
准备工作（导入库、导入数据）import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
sns.set_style("darkgrid")
list_csv = ['Amazon_top_selling_book.csv','breast_cancer_wisconsin.csv','diamonds.csv','insurance.csv','netflix_titles.csv','penguins.csv',
'titanic.csv','winequality-red.csv']
dic_path = r'C:\Users\pandas\Desktop\task\228datasets\datasets'
part_data = pd.read_csv(dic_path+'\\'+list_csv[4])
part_data
| s1 | Movie | Dick Johnson Is Dead | Kirsten Johnson | NaN | United States | September 25, 2021 | 2020 | PG-13 | 90 min | Documentaries | As her father nears the end of his life, filmm... |
| s2 | TV Show | Blood & Water | NaN | Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban... | South Africa | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, TV Dramas, TV Mysteries | After crossing paths at a party, a Cape Town t... |
| s3 | TV Show | Ganglands | Julien Leclercq | Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi... | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Crime TV Shows, International TV Shows, TV Act... | To protect his family from a powerful drug lor... |
| s4 | TV Show | Jailbirds New Orleans | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Docuseries, Reality TV | Feuds, flirtations and toilet talk go down amo... |
| s5 | TV Show | Kota Factory | NaN | Mayur More, Jitendra Kumar, Ranjan Raj, Alam K... | India | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, Romantic TV Shows, TV ... | In a city of coaching centers known to train I... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8807 rows × 12 columns
检测数据情况Hint:该函数用于检测任意DataFrame中缺失值情况
def missing_values_table(df):
mis_val = df.isnull().sum()
mis_val_percent = 100 * df.isnull().sum() / len(df)
mis_val_table = pd.concat([mis_val, mis_val_percent], axis=1)
mis_val_table_ren_columns = mis_val_table.rename(
columns = {0 : 'Missing Values', 1 : '% of Total Values'})
mis_val_table_ren_columns = mis_val_table_ren_columns[
mis_val_table_ren_columns.iloc[:,1] != 0].sort_values(
'% of Total Values', ascending=False).round(1)
print ("Your selected dataframe has " + str(df.shape[1]) + " columns.\n"
"There are " + str(mis_val_table_ren_columns.shape[0]) +
" columns that have missing values.")
return mis_val_table_ren_columns
missing_values_table(part_data)
Your selected dataframe has 12 columns.
There are 6 columns that have missing values.
| 2634 | 29.9 |
| 831 | 9.4 |
| 825 | 9.4 |
| 10 | 0.1 |
| 4 | 0.0 |
| 3 | 0.0 |
参数说明：
labels 就是要删除的行列的名字，用列表给定
axis 默认为0，指删除行，因此删除columns时要指定axis=1；
index 直接指定要删除的行
columns 直接指定要删除的列
inplace=False，默认该删除操作不改变原数据，而是返回一个执行删除操作后的新dataframe；
inplace=True，则会直接在原数据上进行删除操作，删除后无法返回。
方式一：删除指定行或列labels+axis
demo = part_data.drop(['director'], axis=1)
missing_values_table(demo)
Your selected dataframe has 11 columns.
There are 5 columns that have missing values.
| 831 | 9.4 |
| 825 | 9.4 |
| 10 | 0.1 |
| 4 | 0.0 |
| 3 | 0.0 |
df = df.drop(df[].index)
# 删除release_year年份在2009年之前的行
demo = part_data.drop(part_data[part_data["release_year"]<2009].index)
demo.shape
(7624, 12)
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