为什么从带有 Pandas 的 a.CSV 文件中读取的数据在转换为整数后不能使用 matplotlib 绘制？

Question

My Goal

Display a bar chart showing the names durations of the first 30 Netflix shows from a.CSV file

Relevant Code after Trail & Error

names = pd.read_csv("netflix_titles.csv", nrows=31, usecols=[2])
durations = pd.read_csv("netflix_titles.csv", nrows=31, usecols=[9])
durations[['duration']] = durations[['duration']].astype(int)

Then I plot it.

plt.bar(names,durations)
plt.title("Show Durations")
plt.xlabel("Name of Shows")
plt.ylabel("Durations (In Minutes)")
plt.show()

31 rows are read as the first rows are headers. durations is turned into integers as the numbers in the column count as string or something else, and wouldn't work with matplotlib.

Error Message

TypeError: unhashable type: 'numpy.ndarray'

I don't think Numpy applies with what I'm trying to do, so I'm at a dead end here.

Answer 1

This was able to print out a bar chart for the first 31 values

dataset = pd.read_csv("netflix_titles.csv")

names = dataset['title'].head(31)
durations = dataset['duration'].head(31)

plt.bar(names,durations)
plt.title("Show Durations")
plt.xlabel("Name of Shows")
plt.ylabel("Durations (In Minutes)")
plt.show

Answer 2

The problem is that your are making two different DataFrames from the csv file and trying to plot them against each other. While this is possible, a much simpler approach is to create a single Dataframe from the selected columns and rows of the csv file and then plot it as demonstrated below:

import pandas as pd
from matplotlib import pyplot as plt

df = pd.read_csv("netflix_titles.csv", nrows=31, usecols=[2,9])
df.columns = ['name', 'duration']
df['duration'] = df['duration'].astype(int)
df.set_index('name', inplace=True)

df.plot(kind = 'bar')
plt.title("Show Durations")
plt.xlabel("Name of Shows")
plt.ylabel("Durations (In Minutes)")
plt.show()