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
| show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 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... |
| 1 | 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... |
| 2 | 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... |
| 3 | 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... |
| 4 | 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
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.
| Missing Values | % of Total Values | |
|---|---|---|
| director | 2634 | 29.9 |
| country | 831 | 9.4 |
| cast | 825 | 9.4 |
| date_added | 10 | 0.1 |
| rating | 4 | 0.0 |
| duration | 3 | 0.0 |
参数说明：
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.
| Missing Values | % of Total Values | |
|---|---|---|
| country | 831 | 9.4 |
| cast | 825 | 9.4 |
| date_added | 10 | 0.1 |
| rating | 4 | 0.0 |
| duration | 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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