Add materials for Reading and Writing CSV Files in Python

python-csv/README.md

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+# Reading and Writing CSV Files in Python
+
+This folder provides the code examples for the Real Python tutorial [Reading and Writing CSV Files in Python](https://realpython.com/python-csv/).
+
+Consider creating a [Python virtual environment](https://realpython.com/python-virtual-environments-a-primer/) before installing the dependencies:
+
+```shell
+$ python3 -m venv .venv/ --prompt python-csv
+$ source .venv/bin/activate
+(python-csv) $ python -m pip install -r requirements.txt
+```
+
+The scripts read their data files from the current working directory, so run them from inside this folder:
+
+```shell
+(python-csv) $ python read_csv_with_reader.py
+```
+
+Each script holds the code from one section of the tutorial:
+
+| File | Tutorial section |
+| --- | --- |
+| `read_csv_with_reader.py` | Reading CSV Files With `csv` |
+| `read_csv_into_dictionary.py` | Reading CSV Files Into a Dictionary With `csv` |
+| `write_csv_with_writer.py` | Writing CSV Files With `csv` |
+| `write_csv_from_dictionary.py` | Writing CSV File From a Dictionary With `csv` |
+| `read_csv_with_pandas.py` | Reading CSV Files With `pandas` |
+| `write_csv_with_pandas.py` | Writing CSV Files With `pandas` |
+
+The examples that the tutorial shows at the interactive prompt are included in
+`read_csv_with_pandas.py` as `print()` calls, in the same order as the article,
+so that you can run the whole section as a single script.
+
+There are also three data files used throughout the tutorial:
+
+| File | Description |
+| --- | --- |
+| `employee_birthday.csv` | Employee names, departments, and birthday months read by the `csv` examples. |
+| `employee_addresses.csv` | Addresses containing an embedded comma, used to illustrate the optional `reader` parameters. |
+| `hrdata.csv` | Employee hire dates, salaries, and sick days read by the `pandas` examples. |
+
+Running the writing examples creates `employee_file.csv`, `employee_file2.csv`,
+and `hrdata_modified.csv` in this folder. Those files aren't checked in, since
+the tutorial generates them.

python-csv/employee_addresses.csv

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+name,address,date joined
+john smith,1132 Anywhere Lane Hoboken NJ, 07030,Jan 4
+erica meyers,1234 Smith Lane Hoboken NJ, 07030,March 2

python-csv/employee_birthday.csv

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+name,department,birthday month
+John Smith,Accounting,November
+Erica Meyers,IT,March

python-csv/hrdata.csv

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+Name,Hire Date,Salary,Sick Days remaining
+Graham Chapman,03/15/14,50000.00,10
+John Cleese,06/01/15,65000.00,8
+Eric Idle,05/12/14,45000.00,10
+Terry Jones,11/01/13,70000.00,3
+Terry Gilliam,08/12/14,48000.00,7
+Michael Palin,05/23/13,66000.00,8

python-csv/read_csv_into_dictionary.py

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+import csv
+
+with open("employee_birthday.csv", mode="r") as csv_file:
+    csv_reader = csv.DictReader(csv_file)
+    line_count = 0
+    for row in csv_reader:
+        if line_count == 0:
+            print(f"Column names are {', '.join(row)}")
+            line_count += 1
+        print(
+            f"\t{row['name']} works in the {row['department']} "
+            f"department, and was born in {row['birthday month']}."
+        )
+        line_count += 1
+    print(f"Processed {line_count} lines.")

python-csv/read_csv_with_pandas.py

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+import pandas
+
+df = pandas.read_csv("hrdata.csv")
+print(df)
+
+print(type(df["Hire Date"][0]))
+
+df = pandas.read_csv("hrdata.csv", index_col="Name")
+print(df)
+
+df = pandas.read_csv(
+    "hrdata.csv",
+    index_col="Name",
+    parse_dates=["Hire Date"],
+    date_format="%m/%d/%y",
+)
+print(df)
+
+print(type(df["Hire Date"].iloc[0]))
+
+df = pandas.read_csv(
+    "hrdata.csv",
+    index_col="Employee",
+    parse_dates=["Hired"],
+    date_format="%m/%d/%y",
+    header=0,
+    names=["Employee", "Hired", "Salary", "Sick Days"],
+)
+print(df)

python-csv/read_csv_with_reader.py

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+import csv
+
+with open("employee_birthday.csv") as csv_file:
+    csv_reader = csv.reader(csv_file, delimiter=",")
+    line_count = 0
+    for row in csv_reader:
+        if line_count == 0:
+            print(f"Column names are {', '.join(row)}")
+            line_count += 1
+        else:
+            print(
+                f"\t{row[0]} works in the {row[1]} department, and was born in {row[2]}."
+            )
+            line_count += 1
+    print(f"Processed {line_count} lines.")

python-csv/requirements.txt

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+pandas==3.0.5

python-csv/write_csv_from_dictionary.py

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+import csv
+
+with open("employee_file2.csv", mode="w", newline="") as csv_file:
+    fieldnames = ["emp_name", "dept", "birth_month"]
+    writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
+
+    writer.writeheader()
+    writer.writerow(
+        {
+            "emp_name": "John Smith",
+            "dept": "Accounting",
+            "birth_month": "November",
+        }
+    )
+    writer.writerow(
+        {"emp_name": "Erica Meyers", "dept": "IT", "birth_month": "March"}
+    )

python-csv/write_csv_with_pandas.py

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+import pandas
+
+df = pandas.read_csv(
+    "hrdata.csv",
+    index_col="Employee",
+    parse_dates=["Hired"],
+    date_format="%m/%d/%y",
+    header=0,
+    names=["Employee", "Hired", "Salary", "Sick Days"],
+)
+df.to_csv("hrdata_modified.csv")

python-csv/write_csv_with_writer.py

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+import csv
+
+with open("employee_file.csv", mode="w", newline="") as employee_file:
+    employee_writer = csv.writer(
+        employee_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL
+    )
+
+    employee_writer.writerow(["John Smith", "Accounting", "November"])
+    employee_writer.writerow(["Erica Meyers", "IT", "March"])