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Today, I would like to share with you the practical skills of Python data processing, which are relevant knowledge points, detailed content and clear logic. I believe most people still know too much about this knowledge, so share this article for your reference. I hope you can get something after reading this article.

The version of Pandas I use is as follows, which is also imported into the Pandas library by the way.

> > import pandas as pd > pd.__version__'0.25.1'

Make sure that the interpreter and the dataset are in the same directory before you begin:

> import os > os.chdir ('drinksbycountry.csv', IMDB-Movie-Data.csv',' movietweetings', titanic_eda_data.csv', 'dataset') # this is the directory where my dataset is located > titanic_eda_data.csv', () # confirm that the dataset already exists in this directory ['drinksbycountry.csv',' dataset 'movietweetings',' source 'dataset]

After the preparatory work is in place, we will officially begin the journey of data processing skills.

1 Pandas removes a column

Import data

> df = pd.read_csv ("IMDB-Movie-Data.csv") > df.head (1) # Import and display the first line Rank Title Genre. Votes Revenue (Millions) Metascore0 1 Guardians of the Galaxy Action,Adventure,Sci-Fi... 757074 333.13 76.0 [1 rows x 12 columns]

Use the pop method to remove the specified column:

> meta = df.pop ("Title") .to_frame () # remove Title column

Confirm that it has been removed:

> df.head (1) # df becomes 11-column Rank Genre. Revenue (Millions) Metascore0 1 Action,Adventure,Sci-Fi... 333.13 76.0 [1 rows x 11 columns] 2 count the number of words in the title

After pop, you get meta, which displays the first three lines of meta:

> meta.head (3) Title0 Guardians of the Galaxy1 Prometheus2 Split

The title is made up of words, separated by spaces.

# .str.count ("") + 1 get the number of words > meta ["words_count"] = meta ["Title"] .str.count (") + 1 > meta.head (3) # words_count column represents the number of words Title words_count0 Guardians of the Galaxy 41 Prometheus 12 Split 13 Genre frequency statistics

The frequency of the movie Genre is counted below.

> vc = df ["Genre"] .value_counts ()

The Top5 of the movie Genre is shown below. The highest frequency is the Action,Adventure,Sci-Fi class with 50 occurrences, followed by the Drama class with 48 occurrences:

> vc.head () Action,Adventure,Sci-Fi 50Drama 48 Comedy 31Name: Genre, dtype: int64

Show the pie chart of Top5:

> > import matplotlib.pyplot as plt > vc [: 5] .plot (kind='pie') > plt.show ()

These are all the contents of this article entitled "what are the practical skills of Python data processing?" Thank you for reading! I believe you will gain a lot after reading this article. The editor will update different knowledge for you every day. If you want to learn more knowledge, please pay attention to the industry information channel.

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