You can use the following templates to check if a file or a directory exists using Python: (1) Check if a file exists using os.path.isfile: Copy import os.pathfile_exists = os.path.isfile(r”path where the file is stored\file_name.file_extension”)print(file_exists) (2) Check if a directory exists using os.path.isdir: Copy import os.pathdirectory_exists = os.path.isdir(r”path of directory”)print(directory_exists) Steps to Check if a … Read more

To count NaN values in Pandas DataFrame: (1) Under a single DataFrame column: Copy df[“column name”].isna().sum() (2) Under an entire DataFrame: Copy df.isna().sum().sum() (3) Across a single DataFrame row: Copy df.loc[[index value]].isna().sum().sum() The Example Suppose you created the following DataFrame that contains NaN values: Copy import pandas as pdimport numpy as npdata = { “first_set”: … Read more

Here are 2 ways to drop columns with NaN values in Pandas DataFrame: (1) Drop any column that contains at least one NaN: Copy df.dropna(axis=’columns’, inplace=True) (2) Drop column/s where ALL the values are NaN: Copy df.dropna(axis=’columns’, how=’all’, inplace=True) The Example For demonstration purposes, let’s create a DataFrame with 5 columns, where: Here is the … Read more

Here are 3 approaches to convert floats to strings in Pandas DataFrame for: (1) A single DataFrame column using astype(str): Copy df[“DataFrame Column”] = df[“DataFrame Column”].astype(str) (2) A single DataFrame column using apply(str): Copy df[“DataFrame Column”] = df[“DataFrame Column”].apply(str) (3) An entire DataFrame using: Copy df = df.astype(str) 3 Approaches to Convert Floats to Strings … Read more

You can convert floats to integers in Pandas DataFrame using: (1) astype(int): Copy df[“DataFrame Column”] = df[“DataFrame Column”].astype(int) (2) apply(int): Copy df[“DataFrame Column”] = df[“DataFrame Column”].apply(int) In this guide, you’ll see 4 scenarios of converting floats to integers for: 4 Scenarios of Converting Floats to Integers in Pandas DataFrame (1) Convert floats to integers for … Read more

To convert Pandas DataFrame to a dictionary: Copy my_dictionary = df.to_dict() Steps to Convert Pandas DataFrame to a Dictionary Step 1: Create a DataFrame For example, create a DataFrame with two columns: Copy import pandas as pddata = { “Product”: [“Laptop”, “Printer”, “Monitor”, “Tablet”], “Price”: [1200, 100, 300, 150],}df = pd.DataFrame(data)print(df)print(type(df)) You’ll then get the … Read more

To convert Pandas DataFrame to Series using squeeze: Copy df.squeeze() In this guide, you’ll see 3 scenarios of converting: (1) Convert a Single DataFrame Column into a Series To start with a simple example, let’s create a DataFrame with a single column: Copy import pandas as pd data = {“Products”: [“Computer”, “Printer”, “Tablet”, “Chair”, “Desk”]} … Read more

The len() function can be used to count the number of elements in a Python list: Copy len(my_list) 3 Examples of Counting the Number of Elements in a List Example 1: List that Contains Strings To start with a simple example, create a list that contains 5 names: Copy names_list = [“Jeff”, “Ben”, “Maria”, “Sophia”, … Read more

Here is a simple template to create a horizontal bar chart using Matplotlib: Copy import matplotlib.pyplot as plty_axis = [“value_1”, “value_2”, “value_3”, …]x_axis = [“value_1”, “value_2”, “value_3”, …]plt.barh(y_axis, x_axis)plt.title(“title name”)plt.ylabel(“y axis name”)plt.xlabel(“x axis name”)plt.show() Steps to Create Horizontal Bar Chart using Matplotlib Step 1: Gather the data for the chart For example, let’s use the … Read more

In this short guide, you’ll see how to change the order of columns in Pandas DataFrame. Here are the steps: Steps to Change the Order of Columns in Pandas DataFrame Step 1: Prepare the Data for the DataFrame To begin, prepare the data for your DataFrame. For example: Name Age Profession Country Jack 22 Accountant … Read more