[英]Pandas append returns DF with NaN values
我要將數據從列表追加到pandas df。 我一直在輸入NaN。
基於閱讀的內容,我認為可能不得不提及代碼中每一列的數據類型。
dumps = [];features_df = pd.DataFrame()
for i in range (int(len(ids)/50)):
dumps = sp.audio_features(ids[i*50:50*(i+1)])
for i in range (len(dumps)):
print(list(dumps[0].values()))
features_df = features_df.append(list(dumps[0].values()), ignore_index = True)
預期結果,類似-
[0.833,0.539,11,-7.399,0,0.178,0.163,2.1e-06,0.101,0.385,99.947,'audio_features','6MWtB6iiXyIwun0YzU6DFP','spotify:track:6MWtB6iiXyIwun0YzU6DFP',' https:// api。 spotify.com/v1/tracks/6MWtB6iiXyIwun0YzU6DFP ”, ' https://api.spotify.com/v1/audio-analysis/6MWtB6iiXyIwun0YzU6DFP ',149520,4]一行。 實際-
舞蹈能量... duration_ms time_signature
0 NaN NaN ... NaN NaN
1 NaN NaN ... NaN NaN
2 NaN NaN ... NaN NaN
3 NaN NaN ... NaN NaN
4 NaN NaN ... NaN NaN
5 NaN NaN ... NaN NaN
對於所有行
緊密循環中的append()
策略並不是實現此目的的好方法。 相反,您可以構造一個空的DataFrame
,然后使用loc
指定插入點。 應該使用DataFrame
索引。
例如:
import pandas as pd
df = pd.DataFrame(data=[], columns=['n'])
for i in range(100):
df.loc[i] = i
print(df)
time python3 append_df.py
n
0 0
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
real 0m13.178s
user 0m12.287s
sys 0m0.617s
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