Loading data

Load and inspect a dataset with pandas.

Project: weather readings

In this project you'll process five days of temperature and humidity readings step by step: load, clean, compute statistics, write a report. The data is CSV text and some cells are empty:

gun,sicaklik,nem
1,20,40
2,22,
3,,60
4,26,50
5,24,45

In real projects data comes from a file; here we'll read the text like a file with io.StringIO.

np.genfromtxt

np.genfromtxt turns a text table into a numeric array and makes empty cells nan:

veri = np.genfromtxt(io.StringIO(csv), delimiter=",", skip_header=1)
print(veri.shape)              # (5, 3)
print(np.isnan(veri).sum())    # number of empty cells

skip_header=1 skips the header line; if it isn't skipped, the header is also read as a row of nan.

Exercise Load the data

Read the csv text with np.genfromtxt (delimiter=",", skip_header=1). Print the array's shape and the number of empty cells on separate lines.

Show example solution

import io
import numpy as np

csv = "gun,sicaklik,nem\n1,20,40\n2,22,\n3,,60\n4,26,50\n5,24,45\n"

veri = np.genfromtxt(io.StringIO(csv), delimiter=",", skip_header=1)
print(veri.shape)
print(np.isnan(veri).sum())

Test yourself

How many data rows does this CSV have (excluding the header)?
- 5
- 6
- 3
- 4
Show answer

5 — The first line holds the column names; below it are the readings of five days.

Read while skipping the header line.

veri = np.genfromtxt(io.StringIO(csv), delimiter=",", ____=1)

Show answer

veri = np.genfromtxt(io.StringIO(csv), delimiter=",", skip_header=1)

Match the pieces.

io.StringIO

Reads text like a file
delimiter=","

Separator character
skip_header=1

Skips the header
np.isnan

Finds empty cells

Next lesson: Cleaning data

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