问题
I am currently going through the book "Hands-On machine learning... " by Aurèlion Gèron. However, I am getting the following error message: (it is somewhat cumbersome to reproduce because the following two CSV downloads are required: OECD IMF.
Error message:
File "C:\Users\xxx\Miniconda3\lib\site-packages\pandas\core\frame.py", line 4548, in set_index raise KeyError(f"None of {missing} are in the columns")
KeyError: "None of ['Country'] are in the columns"
The code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sklearn.linear_model
oecd_bli = pd.read_csv("BLI_24092020220751169.csv", thousands =',')
gdp_per_capita = pd.read_csv("gdp_per_capita.csv", thousands =',', delimiter ='\t', encoding =' latin1', na_values="n/a")
def prepare_country_stats(oecd_bli, gdp_per_capita):
oecd_bli = oecd_bli[oecd_bli["INEQUALITY"]=="TOT"]
oecd_bli = oecd_bli.pivot(index="Country", columns="Indicator", values="Value")
gdp_per_capita.rename(columns={"2015":"GDP per capita"}, inplace=True)
gdp_per_capita.set_index("Country", inplace=True)
full_country_stats = pd.merge(left=oecd_bli, right=gdp_per_capita,
left_index=True, right_index=True)
full_country_stats.sort_values(by="GDP per capita", inplace=True)
remove_indices = [0, 1, 6, 8, 33, 34, 35]
keep_indices = list(set(range(36)) - set(remove_indices))
return full_country_stats[["GDP per capita", 'Life satisfaction']].iloc[keep_indices]
country_stats = prepare_country_stats(oecd_bli, gdp_per_capita)
X = np.c_[country_stats["GDP per capita"]]
y = np.c_[country_stats["Life satisfaction"]]
# Visualize the data
country_stats.plot( kind ='scatter', X ="GDP per capita", y ='Life satisfaction')
plt.show()
# Select a linear model
model = sklearn.linear_model.LinearRegression()
# Train the model
model.fit(X, y)
# Make a prediction for Cyprus
X_new = [[22587]]
# Cyprus's GDP per capita
print( model.predict(X_new))
However, already in the function I get stuck. The error seems to be related to the set_index
command, which I thought was a very reliable function. Of course, in my CSV file the Country
column is present.
Here is a screenshot of the gdp_per_capita
CSV.
If anyone takes the time to reproduce, it would be highly appreciated.
回答1:
Couple of changes required in your code:
Change this line:
gdp_per_capita = pd.read_csv("gdp_per_capita.csv", thousands =',', delimiter ='\t', encoding =' latin1', na_values="n/a")
to this (remove the encoding='latin1'
):
gdp_per_capita = pd.read_csv("gdp_per_capita.csv", thousands =',', delimiter ='\t', na_values="n/a")
And change this:
country_stats.plot(kind='scatter', X="GDP per capita", y='Life satisfaction')
To this (Capital X to x):
country_stats.plot(kind='scatter', x="GDP per capita", y='Life satisfaction')
I was able to get a scatter plot after these 2 changes:
回答2:
Reading the
gdp_per_capita
csv with'latin'
encoding reads theCountry
column asCountry
. Therefore, I suggest'utf-8'
encoding, which resolves this issue.You had a typo in the
scatterplot
, which @NYC coder has already pointed out.
Try this:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sklearn.linear_model
oecd_bli = pd.read_csv("BLI_26092020152902439.csv", thousands =',')
gdp_per_capita = pd.read_csv("gdp_per_capita.csv", delimiter = '\t', thousands =',', encoding ='utf-8', na_values="n/a")
def prepare_country_stats(oecd_bli, gdp_per_capita):
oecd_bli = oecd_bli[oecd_bli["INEQUALITY"]=="TOT"]
oecd_bli = oecd_bli.pivot(index="Country", columns="Indicator", values="Value")
gdp_per_capita.rename(columns={"2015":"GDP per capita"}, inplace=True)
print(gdp_per_capita)
gdp_per_capita.set_index("Country", inplace=True)
full_country_stats = pd.merge(left=oecd_bli, right=gdp_per_capita,
left_index=True, right_index=True)
full_country_stats.sort_values(by="GDP per capita", inplace=True)
remove_indices = [0, 1, 6, 8, 33, 34, 35]
keep_indices = list(set(range(36)) - set(remove_indices))
return full_country_stats[["GDP per capita", 'Life satisfaction']].iloc[keep_indices]
country_stats = prepare_country_stats(oecd_bli, gdp_per_capita)
X = np.c_[country_stats["GDP per capita"]]
y = np.c_[country_stats["Life satisfaction"]]
# Visualize the data
country_stats.plot( kind ='scatter', x ="GDP per capita", y ='Life satisfaction')
plt.show()
# Select a linear model
model = sklearn.linear_model.LinearRegression()
# Train the model
model.fit(X, y)
# Make a prediction for Cyprus
X_new = [[22587]]
# Cyprus's GDP per capita
print( model.predict(X_new))
Output:
来源:https://stackoverflow.com/questions/64078168/python-pandas-set-index-function-keyerror-none-of-are-in-the-columns