{"id":129156,"date":"2022-10-23T17:10:38","date_gmt":"2022-10-23T17:10:38","guid":{"rendered":"https:\/\/blog.finxter.com\/?p=821905"},"modified":"2022-10-23T17:10:38","modified_gmt":"2022-10-23T17:10:38","slug":"how-to-convert-pandas-dataframe-series-to-numpy-array","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2022\/10\/23\/how-to-convert-pandas-dataframe-series-to-numpy-array\/","title":{"rendered":"How to Convert Pandas DataFrame\/Series to NumPy Array?"},"content":{"rendered":"\n
\n
\n
\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n
\n
<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n
5\/5 – (1 vote) <\/div>\n<\/div>\n

\"\ud83d\udcac\" Programming Challenge<\/strong>: Given a Pandas DataFrame or a Pandas Series object. How to convert them to a NumPy array?<\/p>\n

\n
\"How<\/figure>\n<\/div>\n

In this short tutorial, you’ll learn (1) how to convert a 1D pandas Series<\/strong> to a NumPy<\/a> array, and (2) how to convert a 2D pandas DataFrame<\/strong> to an array. Let’s get started with the first! \"\ud83d\udc47\"<\/p>\n

Convert Pandas Series to NumPy Array<\/h2>\n

First, let’s create a Pandas<\/a> Series.<\/p>\n

import pandas as pd # create dataframe df df = pd.Series([22,21,20,14], name= 'GSTitles', index= ['Nadal','Djokovic','Federer','Sampras'])\nprint(df)\n<\/pre>\n
Here’s the resulting Series df<\/code>:<\/p>\n
Nadal 22\nDjokovic 21\nFederer 20\nSampras 14\nName: GSTitles, dtype: int64<\/pre>\n
Now that we have our Pandas Series, you can convert this to a NumPy Array using the DataFrame.to_numpy()<\/code> method.<\/p>\n
Like so:<\/p>\n
print(df.to_numpy())\n# [22 21 20 14]<\/pre>\n
The resulting object is a NumPy<\/a> array:<\/p>\n
print(type(df.to_numpy()))\n# <class 'numpy.ndarray'><\/pre>\n
\"\u26a1\" Attention<\/strong>: There is also the .values()<\/code> method, but that is being deprecated now – when you look at the Pandas documentation, there is a warning “We recommend using DataFrame.to_numpy<\/code> instead”<\/em>. <\/p>\n
With this method, only the values in the DataFrame or Series will return. The index labels will be removed.<\/p>\n
Here’s how that’ll work:<\/p>\n
print(df.values)\n# [22 21 20 14]<\/pre>\n
This was a 1-dimensional array or a Series. Let’s move on to the 2D case next. \"\ud83d\udc47\"\"\ud83d\udc47\"\"\ud83d\udc47\"<\/p>\n
Convert DataFrame to NumPy Array<\/h2>\n
\"\ud83d\udcac\" Question<\/strong>: Let’s try with a two-dimensional DataFrame — how to convert it to a NumPy array?<\/p>\n
First, let’s print<\/a> the dimension of the previous Series to confirm that it was, indeed, a 1D data structure:<\/p>\n
print(df.ndim)\n# 1<\/pre>\n
Next, you create a 2D DataFrame object:<\/p>\n
import pandas as pd # Create a 2D DataFrame object\ndf2 = pd.DataFrame(data={'Nadal': [2, 14, 2, 4], 'Djokovic': [9, 2, 7, 3], 'Federer': [6, 1, 8, 5], 'Sampras': [2, 0, 7, 5]}, index=['AO', 'F', 'W', 'US']) print(df2)\n<\/pre>\n
Here’s the resulting DataFrame:<\/p>\n
\n\n\n\n\n\n\n\n\n
<\/th>\nNadal<\/th>\nDjokovic<\/th>\nFederer<\/th>\nSampras<\/th>\n<\/tr>\n<\/thead>\n
AO<\/th>\n2<\/td>\n9<\/td>\n6<\/td>\n2<\/td>\n<\/tr>\n
F<\/th>\n14<\/td>\n2<\/td>\n1<\/td>\n0<\/td>\n<\/tr>\n
W<\/th>\n2<\/td>\n7<\/td>\n8<\/td>\n7<\/td>\n<\/tr>\n
US<\/th>\n4<\/td>\n3<\/td>\n5<\/td>\n5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n
Now, let’s dive into the conversion of this DataFrame to a NumPy array by using the DataFrame.to_numpy()<\/code> method.<\/p>\n
# Convert this DataFrame to a NumPy array\nprint(df2.to_numpy())<\/pre>\n
The output shows a NumPy array from the 2D DataFrame — great! \"\ud83d\udc7e\"<\/p>\n
[[ 2 9 6 2] [14 2 1 0] [ 2 7 8 7] [ 4 3 5 5]]<\/pre>\n
You can see that all indexing metadata has been stripped away from the resulting NumPy array!<\/p>\n
Convert Specific Columns from DataFrame to NumPy Array<\/h2>\n
You can also convert specific columns of a Pandas DataFrame by accessing the columns using pandas indexing and calling the .to_numpy()<\/code> method on the resulting view object.<\/p>\n
Here’s an example:<\/p>\n
print(df2[['Djokovic', 'Federer']].to_numpy())<\/pre>\n
The output:<\/p>\n
[[9 6] [2 1] [7 8] [3 5]]<\/pre>\n
Summary<\/h2>\n
You can convert a Pandas DataFrame or a Pandas Series object to a NumPy array by means of the df.to_numpy()<\/code> method. The indexing metadata will be removed.<\/p>\n
You can also convert specific columns of a Pandas DataFrame by accessing the columns using pandas indexing<\/a> and calling the .to_numpy()<\/code> method on the resulting view object.<\/p>\n
\n
Thanks for reading through the whole tutorial! \"\ud83d\ude42\"<\/p>\n","protected":false},"excerpt":{"rendered":"
5\/5 – (1 vote) Programming Challenge: Given a Pandas DataFrame or a Pandas Series object. How to convert them to a NumPy array? In this short tutorial, you’ll learn (1) how to convert a 1D pandas Series to a NumPy array, and (2) how to convert a 2D pandas DataFrame to an array. Let’s get […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[857],"tags":[73,468,528],"class_list":["post-129156","post","type-post","status-publish","format-standard","hentry","category-python-tut","tag-programming","tag-python","tag-tutorial"],"_links":{"self":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/129156","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/comments?post=129156"}],"version-history":[{"count":0,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/129156\/revisions"}],"wp:attachment":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/media?parent=129156"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/categories?post=129156"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/tags?post=129156"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}